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[Перевод] Тонкая настройка Whisper для многоязычного ASR с помощью Hugging Face Transformers

Предлагается пошаговое руководство по дообучению Whisper для любого многоязычного набора данных ASR с использованием Hugging Face 🤗 Transformers. Эта заметка содержит подробные объяснения модели Whisper, набора данных Common Voice и теории дообучения, а также код для выполнения шагов по подготовке данных и дообучению. Для более упрощенной версии с меньшим количеством объяснений, но со всем кодом, см. соответствующий Google Colab.

Содержание

Введение
Дообучение Whisper в Google Colab
1. Подготовка среды
2. Загрузка набора данных
3. Подготовка извлекателя признаков, токенизатора и данных
4. Обучение и оценка
5. Создание демо
Заключительные замечания

Введение

Whisper - это предварительно обученная модель для автоматического распознавания речи (ASR), опубликованная в сентябре 2022 года авторами Alec Radford и др. из OpenAI. В отличие от многих своих предшественников, таких как Wav2Vec 2.0, которые предварительно обучаются на неразмеченных аудиоданных, Whisper предварительно обучается на огромном количестве размеченных аудиоданных с транскрипцией, 680 000 часов, если быть точным. Это на порядок больше данных, чем неразмеченные аудиоданные, используемые для обучения Wav2Vec 2.0 (60 000 часов). Более того, 117 000 часов этих данных для предварительного обучения - это многоязычные данные ASR. Это приводит к тому, что контрольные точки могут быть применены к более чем 96 языкам, многие из которых считаются малоресурсными.

Это количество размеченных данных позволяет Whisper предварительно обучаться непосредственно на задаче распознавания речи, изучая отображение речи в текст из размеченных аудиоданных с транскрипцией. Название Whisper происходит от аббревиатуры "WSPSR", что означает "Web-scale Supervised Pre-training for Speech Recognition" (Масштабное веб-обучение с учителем для распознавания речи). В результате Whisper требует мало дополнительного дообучения, чтобы дать производительную модель ASR. Это в отличие от Wav2Vec 2.0, который предварительно обучается на задаче без учителя - маскированном предсказании. Здесь модель обучается изучать промежуточное отображение от речи к скрытым состояниям из неразмеченных аудиоданных. Хотя предварительное обучение без учителя дает высококачественные представления речи, оно не изучает отображение речи в текст. Это отображение изучается только во время дообучения, поэтому требуется больше дообучения, чтобы добиться конкурентоспособной производительности.

При масштабировании до 680 000 часов размеченных данных для предварительного обучения модели Whisper демонстрируют сильную способность обобщать на многие наборы данных и домены. Предварительно обученные контрольные точки достигают конкурентоспособных результатов по сравнению с передовыми системами ASR, с почти 3% показателем ошибок слов (WER) на подмножестве test-clean LibriSpeech ASR и новым рекордом на TED-LIUM с 4,7% WER (см. таблицу 8 статьи Whisper). Обширные многоязычные знания ASR, полученные Whisper во время предварительного обучения, могут быть использованы для других малоресурсных языков; благодаря тонкой настройке предварительно обученные контрольные точки могут быть адаптированы для конкретных наборов данных и языков, чтобы еще больше улучшить эти результаты.

Whisper - это модель на основе трансформера с encoder-decoder, также называемая моделью sequence-to-sequence. Она отображает последовательность признаков спектрограммы речи на последовательность текстовых токенов. Сначала исходные аудиовходы преобразуются в логарифмическую спектрограмму Мела с помощью извлекателя признаков. Затем трансформерный кодировщик кодирует спектрограмму, формируя последовательность скрытых состояний кодировщика. Наконец, декодер авторегрессивно предсказывает текстовые токены, условно как на предыдущих токенах, так и на скрытых состояниях кодировщика. Рисунок 1 иллюстрирует модель Whisper.

Figure 1: Модель Whisper. Архитектура следует стандартной модели encoder-decoder на основе трансформера. На вход кодировщика подается лог-Мел спектрограмма. Последние скрытые состояния кодировщика передаются на вход декодера через механизмы внимания. Декодер авторегрессивно предсказывает текстовые токены, совместно зависящие от скрытых состояний кодировщика и предыдущих предсказанных токенов. Источник рисунка: OpenAI Whisper Blog.

В модели sequence-to-sequence кодировщик преобразует аудиовходы в набор представлений скрытых состояний, извлекая важные признаки из произнесенной речи. Декодер играет роль языковой модели, обрабатывая представления скрытых состояний и генерируя соответствующие текстовые транскрипции. Включение языковой модели внутри системной архитектуры называется глубоким слиянием. Это противопоставляется поверхностному слиянию, при котором языковая модель комбинируется внешне с кодировщиком, например, с CTC + n-граммами (см. Оценка внутренней языковой модели). При глубоком слиянии вся система может быть обучена end-to-end с одними и теми же данными и функцией потерь, что дает большую гибкость и, как правило, лучшую производительность (см. ESB Benchmark).

Whisper предобучается и дообучается с использованием функции потерь перекрестной энтропии, стандартной функции потерь для обучения систем sequence-to-sequence на задачах классификации. Здесь система обучается правильно классифицировать целевой текстовый токен из предопределенного словаря текстовых токенов.

Для модели Whisper существует пять контрольных точек различных размеров. Четыре самых маленьких обучены либо только на английском, либо на многоязычных данных. Самая большая контрольная точка является многоязычной. Все девять предобученных контрольных точек доступны на Hugging Face Hub. Контрольные точки суммированы в следующей таблице:

В качестве демонстрации мы будем дообучать многоязычную версию маленькой контрольной точки с 244M параметрами (~= 1GB). Что касается наших данных, мы будем обучать и оценивать нашу систему на языке с низкими ресурсами, взятом из набора данных Common Voice. Мы покажем, что с всего лишь 8 часами данных для дообучения, мы можем достичь высокой производительности на этом языке.

Дообучение Whisper в Google Colab

Подготовка среды

Мы будем использовать несколько популярных пакетов Python для дообучения модели Whisper. Мы будем использовать datasets для загрузки и подготовки наших обучающих данных, а также transformers и accelerate для загрузки и обучения нашей модели Whisper. Нам также потребуется пакет soundfile для предварительной обработки аудиофайлов, evaluate и jiwer для оценки производительности нашей модели, и tensorboard для записи наших метрик. Наконец, мы будем использовать gradio для создания яркой демонстрации нашей дообученной модели.

$ pip install --upgrade pip
$ pip install --upgrade datasets transformers accelerate soundfile librosa evaluate jiwer tensorboard gradio

Мы настоятельно рекомендуем вам загружать контрольные точки модели прямо на Hugging Face Hub во время обучения. Hub предоставляет:

Интегрированный контроль версий: вы можете быть уверены, что ни одна контрольная точка модели не будет потеряна во время обучения.
Логи Tensorboard: отслеживайте важные метрики в течение обучения.
Карты моделей: документируйте, что делает модель и ее предполагаемые варианты использования.
Сообщество: простой способ поделиться и сотрудничать с сообществом!

Связывание блокнота с Hub очень просто - достаточно ввести ваш токен аутентификации Hub при запросе. Найдите свой токен аутентификации Hub здесь:

from huggingface_hub import notebook_login

notebook_login()

Ответ:

Login successful
Your token has been saved to /root/.huggingface/token

Загрузка набора данных

Common Voice - это серия наборов данных, созданных с помощью краудсорсинга, где дикторы записывают текст из Википедии на разных языках. Мы будем использовать последнюю версию набора данных Common Voice (версия 11). Что касается нашего языка, мы будем дообучать нашу модель на хинди, индоарийском языке, который говорят на севере, в центре, на востоке и западе Индии. Common Voice 11.0 содержит примерно 12 часов размеченных данных на хинди, 4 из которых являются тестовыми данными.

Давайте перейдем к Hub и посмотрим страницу набора данных Common Voice: mozilla-foundation/common_voice_11_0.

В первый раз, когда мы просматриваем эту страницу, нас попросят принять условия использования. После этого нам будет предоставлен полный доступ к набору данных.

После того, как мы предоставили аутентификацию для использования набора данных, нам будет представлен предварительный просмотр набора данных. Предварительный просмотр набора данных показывает нам первые 100 образцов набора данных. Более того, он загружен аудиообразцами, которые мы можем слушать в реальном времени. Мы можем выбрать подмножество Common Voice на хинди, установив подмножество на hi с помощью выпадающего меню (hi - это код идентификатора языка для хинди):

Если мы нажмем кнопку воспроизведения на первом образце, мы сможем послушать аудио и увидеть соответствующий текст. Просмотрите образцы для обучающих и тестовых наборов, чтобы лучше понять аудио- и текстовые данные, с которыми мы работаем. Вы можете сказать по интонации и стилю, что записи взяты из озвученной речи. Вы также, вероятно, заметите большое разнообразие дикторов и качества записи, общую черту данных, собранных с помощью краудсорсинга.

Используя 🤗 Datasets, загрузка и подготовка данных чрезвычайно проста. Мы можем загрузить и подготовить разделы Common Voice всего в одну строку кода. Поскольку хинди является языком с очень низкими ресурсами, мы объединим обучающие (train) и проверочные (validation) разделы, чтобы получить примерно 8 часов обучающих данных. Мы будем использовать 4 часа тестовых (test) данных в качестве отложенного тестового набора:

from datasets import load_dataset, DatasetDict

common_voice = DatasetDict()

common_voice["train"] = load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="train+validation", use_auth_token=True)
common_voice["test"] = load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="test", use_auth_token=True)

print(common_voice)

Ответ:

DatasetDict({
    train: Dataset({
        features: ['client_id', 'path', 'audio', 'sentence', 'up_votes', 'down_votes', 'age', 'gender', 'accent', 'locale', 'segment'],
        num_rows: 6540
    })
    test: Dataset({
        features: ['client_id', 'path', 'audio', 'sentence', 'up_votes', 'down_votes', 'age', 'gender', 'accent', 'locale', 'segment'],
        num_rows: 2894
    })
})

Большинство наборов данных ASR предоставляют только входные аудиообразцы (audio) и соответствующий транскрибированный текст (sentence). Common Voice содержит дополнительную информацию метаданных, такую как акцент (accent) и местоположение (locale), которую мы можем игнорировать для ASR. Стараясь сделать блокнот максимально универсальным, мы рассматриваем только входное аудио и транскрибированный текст для дообучения, отбрасывая дополнительную информацию метаданных:

common_voice = common_voice.remove_columns(["accent", "age", "client_id", "down_votes", "gender", "locale", "path", "segment", "up_votes"])

Common Voice - это только один из многоязычных наборов данных ASR, которые мы можем загрузить с Hub - у нас есть гораздо больше доступных наборов данных! Чтобы просмотреть диапазон доступных наборов данных для распознавания речи, перейдите по ссылке: ASR Datasets on the Hub.

Подготовка извлекателя признаков, токенизатора и данных

Конвейер ASR можно разложить на три компонента:

Извлекатель признаков, который предварительно обрабатывает входные аудиоданные
Модель, которая выполняет отображение sequence-to-sequence
Токенизатор, который обрабатывает выходные данные модели в текстовый формат

В 🤗 Transformers, модель Whisper имеет связанный с ней извлекатель признаков и токенизатор, называемые соответственно WhisperFeatureExtractor и WhisperTokenizer.

Мы подробно рассмотрим извлекатель признаков и токенизатор!

Загрузка WhisperFeatureExtractor

Речь представляет собой одномерный массив, который меняется со временем. Значение массива в любой данной точке времени - это амплитуда сигнала в этой точке. Исходя только из информации об амплитуде, мы можем восстановить спектр частот аудио и восстановить все акустические признаки.

Поскольку речь непрерывна, она содержит бесконечное количество значений амплитуды. Это вызывает проблемы для компьютерных устройств, которые ожидают конечные массивы. Таким образом, мы дискретизируем наш речевой сигнал, выбирая значения из нашего сигнала с фиксированными временными шагами. Интервал, с которым мы выбираем наше аудио, известен как частота дискретизации и обычно измеряется в выборках/сек или Герцах (Гц). Выборка с более высокой частотой дискретизации приводит к лучшему приближению непрерывного речевого сигнала, но также требует хранения большего количества значений в секунду.

Крайне важно, чтобы мы согласовали частоту дискретизации наших аудиовходов с ожидаемой частотой дискретизации нашей модели, поскольку аудиосигналы с разными частотами дискретизации имеют очень разные распределения. Аудиообразцы должны обрабатываться только с правильной частотой дискретизации. В противном случае это может привести к неожиданным результатам! Например, если взять аудиообразец с частотой дискретизации 16 кГц и прослушать его с частотой дискретизации 8 кГц, звук будет воспроизводиться как будто на половинной скорости. Точно так же передача аудио с неправильной частотой дискретизации может сбить с толку модель ASR, которая ожидает одну частоту дискретизации и получает другую. Извлекатель признаков Whisper ожидает аудиовходы с частотой дискретизации 16 кГц, поэтому нам нужно согласовать наши входы с этим значением. Мы не хотим случайно обучить систему ASR на замедленной речи!

Извлекатель признаков Whisper выполняет две операции. Сначала он дополняет/обрезает пакет аудиообразцов так, чтобы все образцы имели длину входа 30 секунд. Образцы, короче 30 секунд, дополняются до 30 секунд путем добавления нулей в конец последовательности (нули в аудиосигнале соответствуют отсутствию сигнала или тишине). Образцы, длиннее 30 секунд, обрезаются до 30 секунд. Поскольку все элементы в пакете дополняются/обрезаются до максимальной длины во входном пространстве, нам не требуется маска внимания при передаче аудиовходов в модель Whisper. Whisper уникален в этом отношении - с большинством аудиомоделей вы можете ожидать предоставления маски внимания, которая детализирует, где последовательности были дополнены, и, следовательно, где они должны быть проигнорированы в механизме самовнимания. Whisper обучен работать без маски внимания и напрямую выводить из речевых сигналов, где игнорировать входы.

Вторая операция, которую выполняет извлекатель признаков Whisper, - это преобразование дополненных аудиомассивов в логарифмические спектрограммы Mel. Эти спектрограммы - визуальное представление частот сигнала, похожее на преобразование Фурье. Пример спектрограммы показан на рисунке 2. Вдоль оси y находятся каналы Mel, которые соответствуют определенным частотным корзинам. Вдоль оси x - время. Цвет каждого пикселя соответствует логарифмической интенсивности этой частотной корзины в данное время. Логарифмическая спектрограмма Mel - это форма ввода, ожидаемая моделью Whisper.

Каналы Mel (частотные корзины) являются стандартными в обработке речи и выбраны для приближения к человеческому слуховому диапазону. Все, что нам нужно знать для дообучения Whisper, - это то, что спектрограмма - это визуальное представление частот в речевом сигнале. Для получения более подробной информации о каналах Mel обратитесь к Mel-frequency cepstrum.

Рисунок 2: Преобразование выборочного аудиомассива в логарифмическую спектрограмму Mel. Слева: выборочный одномерный аудиосигнал. Справа: соответствующая логарифмическая спектрограмма Mel. Источник рисунка: Блог Google SpecAugment.

К счастью для нас, извлекатель признаков Whisper от 🤗 Transformers выполняет как дополнение, так и преобразование спектрограммы всего в одну строку кода! Давайте загрузим извлекатель признаков из предварительно обученной контрольной точки, чтобы подготовить его для наших аудиоданных:

from transformers import WhisperFeatureExtractor

feature_extractor = WhisperFeatureExtractor.from_pretrained("openai/whisper-small")

Загрузка WhisperTokenizer

Теперь давайте посмотрим, как загрузить токенизатор Whisper. Модель Whisper выводит текстовые токены, которые указывают индекс предсказанного текста среди словаря элементов словаря. Токенизатор отображает последовательность текстовых токенов на фактическую текстовую строку (например, [1169, 3797, 3332] -> "the cat sat").

Традиционно, когда мы используем модели только с кодировщиком для ASR, мы декодируем с использованием классификации по временной связности (CTC). Здесь нам требуется обучить токенизатор CTC для каждого набора данных, который мы используем. Одно из преимуществ использования архитектуры encoder-decoder состоит в том, что мы можем напрямую использовать токенизатор из предварительно обученной модели.

Токенизатор Whisper предварительно обучен на транскрипциях для 96 предварительно обученных языков. Следовательно, он имеет обширный byte-pair, который подходит для почти всех многоязычных приложений ASR. Для хинди мы можем загрузить токенизатор и использовать его для дообучения без каких-либо дальнейших модификаций. Нам просто нужно указать целевой язык и задачу. Эти аргументы информируют токенизатор о том, что нужно добавить токены языка и задачи в начало закодированных последовательностей меток:

from transformers import WhisperTokenizer

tokenizer = WhisperTokenizer.from_pretrained("openai/whisper-small", language="Hindi", task="transcribe")

Совет: блог-пост можно адаптировать для перевода речи, установив задачу на "translate" и язык на язык целевого текста в предыдущей строке. Это добавит соответствующие токены задачи и языка для перевода речи при предварительной обработке набора данных.

Мы можем проверить, что токенизатор правильно кодирует символы хинди, закодировав и декодировав первый образец набора данных Common Voice. При кодировании транскрипций токенизатор добавляет "специальные токены" в начало и конец последовательности, включая токены начала/конца транскрипта, токен языка и токены задач (как указано в аргументах на предыдущем шаге). При декодировании идентификаторов меток у нас есть возможность "пропустить" эти специальные токены, что позволяет нам вернуть строку в исходной форме ввода.

input_str = common_voice["train"][0]["sentence"]
labels = tokenizer(input_str).input_ids
decoded_with_special = tokenizer.decode(labels, skip_special_tokens=False)
decoded_str = tokenizer.decode(labels, skip_special_tokens=True)

print(f"Input:                 {input_str}")
print(f"Decoded w/ special:    {decoded_with_special}")
print(f"Decoded w/out special: {decoded_str}")
print(f"Are equal:             {input_str == decoded_str}")

Ответ:

Input:                 खीर की मिठास पर गरमाई बिहार की सियासत, कुशवाहा ने दी सफाई
Decoded w/ special:    <|startoftranscript|><|hi|><|transcribe|><|notimestamps|>खीर की मिठास पर गरमाई बिहार की सियासत, कुशवाहा ने दी सफाई<|endoftext|>
Decoded w/out special: खीर की मिठास पर गरमाई बिहार की सियासत, कुशवाहा ने दी सफाई
Are equal:             True

Объединение для создания WhisperProcessor

Для упрощения использования извлекателя признаков и токенизатора мы можем объединить оба в один класс WhisperProcessor. Этот объект процессора наследуется от WhisperFeatureExtractor и WhisperProcessor и может использоваться на аудиовходах и прогнозах модели по мере необходимости. Таким образом, нам нужно отслеживать только два объекта во время обучения: processor и model:

from transformers import WhisperProcessor

processor = WhisperProcessor.from_pretrained("openai/whisper-small", language="Hindi", task="transcribe")

Подготовка данных

Давайте распечатаем первый пример набора данных Common Voice, чтобы увидеть, в какой форме находятся данные:

print(common_voice["train"][0])

Ответ:

{'audio': {'path': '/home/sanchit_huggingface_co/.cache/huggingface/datasets/downloads/extracted/607848c7e74a89a3b5225c0fa5ffb9470e39b7f11112db614962076a847f3abf/cv-corpus-11.0-2022-09-21/hi/clips/common_voice_hi_25998259.mp3',
           'array': array([0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ..., 9.6724887e-07,
       1.5334779e-06, 1.0415988e-06], dtype=float32),
           'sampling_rate': 48000},
 'sentence': 'खीर की मिठास पर गरमाई बिहार की सियासत, कुशवाहा ने दी सफाई'}

Мы видим, что у нас есть одномерный входной аудиомассив и соответствующая целевая транскрипция. Мы много говорили о важности частоты дискретизации и о том, что мы должны согласовать частоту дискретизации нашего аудио с частотой дискретизации модели Whisper (16 кГц). Поскольку наше входное аудио дискретизируется с частотой 48 кГц, нам нужно уменьшить ее до 16 кГц перед передачей в извлекатель признаков Whisper.

Мы установим аудиовходы на правильную частоту дискретизации с помощью метода cast_column набора данных. Эта операция не изменяет аудио на месте, а скорее сигнализирует наборам данных (datasets) о ресемплировании аудиообразцов на лету при первой загрузке:

from datasets import Audio

common_voice = common_voice.cast_column("audio", Audio(sampling_rate=16000))

Перезагрузка первого аудиообразца в наборе данных Common Voice приведет его к желаемой частоте дискретизации:

print(common_voice["train"][0])

Ответ:

{'audio': {'path': '/home/sanchit_huggingface_co/.cache/huggingface/datasets/downloads/extracted/607848c7e74a89a3b5225c0fa5ffb9470e39b7f11112db614962076a847f3abf/cv-corpus-11.0-2022-09-21/hi/clips/common_voice_hi_25998259.mp3',
           'array': array([ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00, ...,
       -3.4206650e-07,  3.2979898e-07,  1.0042874e-06], dtype=float32),
           'sampling_rate': 16000},
 'sentence': 'खीर की मिठास पर गरमाई बिहार की सियासत, कुशवाहा ने दी सफाई'}

Отлично! Мы видим, что частота дискретизации была уменьшена до 16 кГц. Значения массива также изменились, так как теперь у нас примерно одно значение амплитуды на каждые три, которые были раньше.

Теперь мы можем написать функцию для подготовки наших данных для модели:

Мы загружаем и ресемплируем аудиоданные, вызывая batch["audio"]. Как объяснялось выше, 🤗 Datasets выполняет все необходимые операции ресемплирования на лету.
Мы используем извлекатель признаков для вычисления входных признаков логарифмической спектрограммы Mel из нашего одномерного аудиомассива.
Мы кодируем транскрипции в идентификаторы меток с помощью токенизатора.

def prepare_dataset(batch):
    # load and resample audio data from 48 to 16kHz
    audio = batch["audio"]

    # compute log-Mel input features from input audio array
    batch["input_features"] = feature_extractor(audio["array"], sampling_rate=audio["sampling_rate"]).input_features[0]

    # encode target text to label ids
    batch["labels"] = tokenizer(batch["sentence"]).input_ids
    return batch

Мы можем применить функцию подготовки данных ко всем нашим обучающим примерам, используя метод .map набора данных:

common_voice = common_voice.map(prepare_dataset, remove_columns=common_voice.column_names["train"], num_proc=4)

Отлично! Теперь у нас есть полностью подготовленные данные для обучения! Давайте продолжим и посмотрим, как мы можем использовать эти данные для дообучения Whisper.

Примечание: В настоящее время наборы данных (datasets) используют как torchaudio, так и librosa для загрузки аудио и ресемплирования. Если вы хотите реализовать свою собственную настройку загрузки/выборки данных, вы можете использовать столбец "path" для получения пути к аудиофайлу и игнорировать столбец "audio".

Обучение и оценка

Теперь, когда мы подготовили наши данные, мы готовы погрузиться в процесс обучения. 🤗 Trainer выполнит большую часть работы за нас. Все, что нам нужно сделать, это:

Определить сборщик данных: сборщик данных берет наши предварительно обработанные данные и подготавливает тензоры PyTorch, готовые для модели.
Метрики оценки: во время оценки мы хотим оценить модель с использованием метрики ошибки на словах - word error rate (WER). Нам нужно определить функцию compute_metrics, которая обрабатывает этот расчет.
Загрузить предварительно обученную контрольную точку: нам нужно загрузить предварительно обученную контрольную точку и правильно настроить ее для обучения.
Определить аргументы обучения: они будут использоваться 🤗 Trainer при построении графика обучения.

После того, как мы дообучили модель, мы оценим ее на тестовых данных, чтобы убедиться, что мы правильно обучили ее транскрибировать речь на хинди.

Определить сборщик данных

Сборщик данных для модели речи sequence-to-sequence уникален тем, что он обрабатывает input_features и labels независимо: input_features должны обрабатываться извлекателем признаков, а labels - токенизатором.

Следует заметить, что input_features уже дополнены до 30 секунд и преобразованы в логарифмическую спектрограмму Mel фиксированного размера, поэтому все, что нам нужно сделать, это преобразовать их в пакетные тензоры PyTorch. Мы делаем это с помощью метода .pad извлекателя признаков с return_tensors=pt. Обратите внимание, что здесь не применяется дополнительное дополнение, поскольку входы имеют фиксированный размер, input_features просто преобразуются в тензоры PyTorch.

С другой стороны, labels не дополнены. Сначала мы дополняем последовательности до максимальной длины в пакете с помощью метода .pad токенизатора. Затем токены дополнения заменяются на -100, чтобы эти токены не учитывались при вычислении потерь. Затем мы вырезаем токен начала транскрипта из начала последовательности меток, так как мы добавляем его позже во время обучения.

Мы можем использовать WhisperProcessor, который мы определили ранее, для выполнения операций как извлекателя признаков, так и токенизатора:

import torch

from dataclasses import dataclass
from typing import Any, Dict, List, Union

@dataclass
class DataCollatorSpeechSeq2SeqWithPadding:
    processor: Any

    def __call__(self, features: List[Dict[str, Union[List[int], torch.Tensor]]]) -> Dict[str, torch.Tensor]:
        # split inputs and labels since they have to be of different lengths and need different padding methods
        # first treat the audio inputs by simply returning torch tensors
        input_features = [{"input_features": feature["input_features"]} for feature in features]
        batch = self.processor.feature_extractor.pad(input_features, return_tensors="pt")

        # get the tokenized label sequences
        label_features = [{"input_ids": feature["labels"]} for feature in features]
        # pad the labels to max length
        labels_batch = self.processor.tokenizer.pad(label_features, return_tensors="pt")

        # replace padding with -100 to ignore loss correctly
        labels = labels_batch["input_ids"].masked_fill(labels_batch.attention_mask.ne(1), -100)

        # if bos token is appended in previous tokenization step,
        # cut bos token here as it's append later anyways
        if (labels[:, 0] == self.processor.tokenizer.bos_token_id).all().cpu().item():
            labels = labels[:, 1:]

        batch["labels"] = labels

        return batch

Давайте инициализируем коллатор данных, который мы только что определили:

data_collator = DataCollatorSpeechSeq2SeqWithPadding(processor=processor)

Метрики оценки

Далее мы определяем метрику оценки, которую будем использовать на нашем наборе данных для оценки. Мы будем использовать метрику ошибки на словах (WER), "де-факто" метрику для оценки систем ASR. Для получения дополнительной информации обратитесь к документации WER. Мы загрузим метрику WER из 🤗 Evaluate:

import evaluate

metric = evaluate.load("wer")

Затем нам просто нужно определить функцию, которая принимает наши прогнозы модели и возвращает метрику WER. Эта функция, называемая compute_metrics, сначала заменяет -100 на pad_token_id в label_ids (отменяя шаг, который мы применили в сборщике данных, чтобы правильно игнорировать дополненные токены при потерях). Затем он декодирует предсказанные идентификаторы меток в строки. Наконец, он вычисляет WER между прогнозами и эталонными метками:

def compute_metrics(pred):
    pred_ids = pred.predictions
    label_ids = pred.label_ids

    # replace -100 with the pad_token_id
    label_ids[label_ids == -100] = tokenizer.pad_token_id

    # we do not want to group tokens when computing the metrics
    pred_str = tokenizer.batch_decode(pred_ids, skip_special_tokens=True)
    label_str = tokenizer.batch_decode(label_ids, skip_special_tokens=True)

    wer = 100 * metric.compute(predictions=pred_str, references=label_str)

    return {"wer": wer}

Загрузка предварительно обученной контрольной точки

Теперь давайте загрузим предварительно обученную контрольную точку Whisper small. Опять же, это тривиально с использованием 🤗 Transformers!

from transformers import WhisperForConditionalGeneration

model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-small")

У модели Whisper есть идентификаторы токенов, которые принудительно выводятся как выходы модели перед началом авторегрессивного генерирования (forced_decoder_ids). Эти идентификаторы токенов контролируют язык транскрипции и задачу для ASR с нулевым выстрелом. Для дообучения мы установим эти идентификаторы в None, так как мы будем обучать модель предсказывать правильный язык (хинди) и задачу (транскрипцию). Есть также токены, которые полностью подавляются во время генерации (suppress_tokens). Эти токены имеют свои логарифмические вероятности, установленные в -inf, так что они никогда не выбираются. Мы переопределим эти токены в пустой список, что означает, что никакие токены не подавляются:

model.config.forced_decoder_ids = None
model.config.suppress_tokens = []

Определение аргументов обучения

На последнем шаге мы определяем все параметры, связанные с обучением. Ниже объясняется подмножество параметров:

output_dir: локальный каталог, в котором сохраняются веса модели. Это также будет название репозитория на Hugging Face Hub.
generation_max_length: максимальное количество токенов для авторегрессивного генерирования во время оценки.
save_steps: во время обучения промежуточные контрольные точки будут сохраняться и асинхронно загружаться на Hub каждые save_steps шагов обучения.
eval_steps: во время обучения оценка промежуточных контрольных точек будет выполняться каждые eval_steps шагов обучения.
report_to: где сохранять журналы обучения. Поддерживаются платформы "azure_ml", "comet_ml", "mlflow", "neptune", "tensorboard" и "wandb". Выберите свою любимую или оставьте "tensorboard", чтобы вести журнал на Hub.

Для получения более подробной информации о других аргументах обучения обратитесь к документации Seq2SeqTrainingArguments.

from transformers import Seq2SeqTrainingArguments

training_args = Seq2SeqTrainingArguments(
    output_dir="./whisper-small-hi",  # change to a repo name of your choice
    per_device_train_batch_size=16,
    gradient_accumulation_steps=1,  # increase by 2x for every 2x decrease in batch size
    learning_rate=1e-5,
    warmup_steps=500,
    max_steps=4000,
    gradient_checkpointing=True,
    fp16=True,
    evaluation_strategy="steps",
    per_device_eval_batch_size=8,
    predict_with_generate=True,
    generation_max_length=225,
    save_steps=1000,
    eval_steps=1000,
    logging_steps=25,
    report_to=["tensorboard"],
    load_best_model_at_end=True,
    metric_for_best_model="wer",
    greater_is_better=False,
    push_to_hub=True,
)

Примечание: если вы не хотите загружать контрольные точки модели в Hub, установите push_to_hub=False.

Мы можем передать аргументы обучения в 🤗 Trainer вместе с нашей моделью, набором данных, коллатором данных и функцией compute_metrics:

from transformers import Seq2SeqTrainer

trainer = Seq2SeqTrainer(
    args=training_args,
    model=model,
    train_dataset=common_voice["train"],
    eval_dataset=common_voice["test"],
    data_collator=data_collator,
    compute_metrics=compute_metrics,
    tokenizer=processor.feature_extractor,
)

И с этим мы готовы приступить к тренировкам!

Обучение

Чтобы начать обучение, просто выполните команду:

trainer.train()

Обучение займет примерно 5-10 часов в зависимости от вашего GPU или того, который выделен в Google Colab. В зависимости от вашего GPU, возможно, вы столкнетесь с ошибкой "out-of-memory" CUDA при начале обучения. В этом случае вы можете уменьшить per_device_train_batch_size инкрементно на множители 2 и использовать gradient_accumulation_steps для компенсации.

Наш лучший WER составляет 32,0% - неплохо для 8 часов обучающих данных! Большой вопрос в том, как это сравнивается с другими системами ASR. Для этого мы можем просмотреть hf-speech-bench, таблицу лидеров, которая классифицирует модели по языку и набору данных, а затем ранжирует их в соответствии с их WER.

Наша модель, прошедшая тонкую настройку, значительно превосходит по производительности "нулевой выстрел" small контрольной точки Whisper, что подчеркивает сильные возможности передачи обучения Whisper.

Мы можем автоматически отправить нашу контрольную точку на доску лидеров, когда мы отправляем результаты обучения на Hub - нам просто нужно установить соответствующие ключевые аргументы (kwargs). Вы можете изменить эти значения в соответствии с вашим набором данных, языком и названием модели.

kwargs = {
    "dataset_tags": "mozilla-foundation/common_voice_11_0",
    "dataset": "Common Voice 11.0",  # a 'pretty' name for the training dataset
    "dataset_args": "config: hi, split: test",
    "language": "hi",
    "model_name": "Whisper Small Hi - Sanchit Gandhi",  # a 'pretty' name for your model
    "finetuned_from": "openai/whisper-small",
    "tasks": "automatic-speech-recognition",
    "tags": "hf-asr-leaderboard",
}

Результаты обучения теперь можно загрузить на Hub. Для этого выполните команду push_to_hub.

trainer.push_to_hub(**kwargs)

Теперь вы можете поделиться этой моделью с кем угодно, используя ссылку на Hub. Они также могут загрузить ее с идентификатором "ваше-имя-пользователя/выбранное-вами-имя", например:

from transformers import WhisperForConditionalGeneration, WhisperProcessor

model = WhisperForConditionalGeneration.from_pretrained("sanchit-gandhi/whisper-small-hi")
processor = WhisperProcessor.from_pretrained("sanchit-gandhi/whisper-small-hi")

Хотя дообученная модель дает удовлетворительные результаты на тестовых данных Common Voice на хинди, она отнюдь не оптимальна. Цель этого блокнота - продемонстрировать, как предварительно обученные контрольные точки Whisper могут быть дообучены на любом многоязычном наборе данных ASR. Результаты, вероятно, могут быть улучшены путем оптимизации гиперпараметров обучения, таких как скорость обучения и исключение, а также использования более крупной предварительно обученной контрольной точки (medium или large).

Создание демо

Теперь, когда мы дообучили нашу модель, мы можем создать демо, чтобы продемонстрировать ее возможности в области ASR! Мы будем использовать конвейер (pipeline) 🤗 Transformers, который заботится обо всем конвейере ASR, начиная от предварительной обработки аудиовходов и заканчивая декодированием прогнозов модели. Мы создадим наше интерактивное демо с помощью Gradio. Gradio, возможно, самый простой способ создания демонстраций машинного обучения; с Gradio мы можем создать демо всего за несколько минут!

Запуск приведенного ниже примера сгенерирует демо Gradio, где мы сможем записывать речь через микрофон нашего компьютера и вводить ее в нашу дообученную модель Whisper для транскрибации соответствующего текста:

from transformers import pipeline
import gradio as gr

pipe = pipeline(model="sanchit-gandhi/whisper-small-hi")  # change to "your-username/the-name-you-picked"

def transcribe(audio):
    text = pipe(audio)["text"]
    return text

iface = gr.Interface(
    fn=transcribe,
    inputs=gr.Audio(source="microphone", type="filepath"),
    outputs="text",
    title="Whisper Small Hindi",
    description="Realtime demo for Hindi speech recognition using a fine-tuned Whisper small model.",
)

iface.launch()

Заключительные замечания

Мы рассмотрели пошаговое руководство по дообучению Whisper для многоязычного ASR с использованием 🤗 Datasets, Transformers и Hugging Face Hub. Обратитесь к Google Colab, если вы хотите попробовать дообучение самостоятельно. Если вас интересует дообучение других моделей Transformers, как для английского, так и для многоязычного ASR, обязательно ознакомьтесь с примерами скриптов в examples/pytorch/speech-recognition.

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25 дек. 2023 г.

22.06.26 21:51 kimberlyhebert786

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06.07.26 16:33 Jaran Løvlien

A heartfelt thank you to RESQPRO FIRM for their commitment and professionalism throughout the investigation of my case. Their team worked diligently and helped recover assets valued at $88,000, which were returned to my wallet. I truly appreciate their support, clear communication, and dedication, and I'm grateful for the assistance I received. Contact: Email: [email protected] Telegram: @Resqprofirm WhatsApp: +1 985 296 9146
07.07.26 18:00 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
07.07.26 18:01 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
09.07.26 19:06 Toivo Walli

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13.07.26 23:49 [email protected]

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16.07.26 21:38 patricialovick86

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16.07.26 21:38 patricialovick86

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17.07.26 20:12 martinsjude080

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18.07.26 17:12 Malthe Larsen

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18.07.26 23:51 bernalzenaida

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19.07.26 04:10 Fraddy Pual

I can't thank Fundsretriever enough for everything they did for me. My name is Vanessa Conway, and I'm here to tell you my story of how I recovered money I never thought I'd see again. A few months ago, I put a significant amount of money into what looked like a genuine online investment company. At first, it felt real—they showed me fake profits and convinced me to invest even more. But when I tried to cash out, they went quiet and started asking for extra fees. That's when it hit me—I had been scammed. I was heartbroken, frustrated, and didn't know where to turn. That money was my savings—months of hard work gone. Then I found Fundsretriever online. I reached out, hoping for a miracle. Right away, their team made me feel heard. They were responsive, knowledgeable, and walked me through everything. They didn't just take my case—they took it seriously and kept me in the loop every step of the way. I finally felt like I had real experts fighting for me. And guess what? They actually got my money back. It wasn't instant, and it took teamwork, but it happened. When I saw those funds returned, I cried with joy. I'm sharing this so that anyone else out there who's been scammed knows—don't lose hope. Do your research before investing, and stay far away from platforms that promise too much too fast. And if you've already been stung, don't wait—get professional help immediately. Thank you, Fundsretriever, from the bottom of my heart. You didn't just recover my money—you restored my faith. — Vanessa Conway 📧 [email protected] 📱 WhatsApp: +16035121448 💬 Telegram: @Fundsretriever
19.07.26 19:53 kimberlyhebertt6877

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
19.07.26 19:53 kimberlyhebertt6877

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
19.07.26 19:54 kimberlyhebertt6877

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30.07.26 00:04 Ahmed

A really cool analysis, thank you. I was especially struck by how strictly the order is defined: data processing and formatting come first, with color only at the very end. This really saves you from the typical mistake of "first a pretty palette, then we figure out what the chart is for." And the palette validator with OKLCH + colorblindness check is absolutely fantastic; you almost never see that in regular tools. By the way, while reading about rank-trajectory and the logarithmic scale, I immediately remembered how convenient it is to analyze dynamics on charts in ExpertOption—I've been trading there for quite some time now. When the data is well visualized, decisions are noticeably easier and more relaxed. I also liked the point about "no more than eight colors" and the dual-axis ban. Strict restrictions sometimes actually produce better results than complete freedom. I'll try this approach myself.
30.07.26 17:27 wendytaylor015

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30.07.26 17:27 wendytaylor015

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31.07.26 16:21 rssllhrnsb

I learned an important lesson after investing in what appeared to be a genuine opportunity. Unfortunately, I was unable to access my funds, which reinforced the importance of carrying out thorough due diligence, checking whether an investment is appropriately regulated, and seeking qualified professional advice rather than relying solely on online reviews or testimonials. During the process of addressing my case, I worked with Mrs. Doris Ashley, who communicated clearly, provided regular updates, and handled the matter in a professional manner. According to my experience, I have recovered $50,000 so far, while efforts to resolve the remaining balance are still in progress. If you wish to contact her, the details I used are: Mrs. Tatiana Sorina TEXT : (tatianasorina06 at G.Ma IL ..c 0 m ) Before committing money to any investment, take time to verify the legitimacy of the platform, confirm any relevant regulatory authorisations, and avoid investing more than you can comfortably afford to lose.
01.08.26 15:05 keithwilson9899

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01.08.26 15:05 keithwilson9899

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03.08.26 20:05 Philip

I was a victim of a crypto theft involving a Pink Drainer, which resulted in the theft of my Wrapped Bitcoin (WBTC) from my Polygon network. The experience was incredibly frustrating and distressing, as I had no idea how to recover my funds. Unfortunately, by the time I noticed the theft, the funds had already been drained to an address that I had no control over, making it seem like an irreversible situation.The attack happened when I clicked on what appeared to be a legitimate link. I didn’t realize at the time that it was a phishing attempt designed to siphon off my private keys and access my wallet. The Pink Drainer, a type of malicious script used by attackers, is specifically designed to exploit such vulnerabilities in crypto wallets. The moment I realized that my WBTC had been drained from my Polygon network. I felt completely helpless, as I didn’t have direct access to the thief's address, and there was no way to reverse the transaction on my own at that point, I started searching for ways to recover my funds, but most resources only offered generic advice that wasn’t practical in this particular case. I quickly realized that if I wanted to have any hope of getting my assets back, I would need professional assistance. After some research, I came across a reliable and trusted recovery team called Aspen Recovery Experts. Their expertise in cryptocurrency recovery, especially in cases like mine, seemed promising.I decided to reach out to Aspen Recovery Experts, and I’m incredibly grateful that I did. Their team of crypto recovery experts was able to help me trace the stolen funds and identify the path the funds took after they left my wallet. Using advanced tools and techniques, they were able to track the transactions on the blockchain, helping me understand where my WBTC had been sent. More importantly, they worked tirelessly to assist me in contacting the necessary parties and even interfaced with blockchain analysts to help facilitate the recovery process.Thanks to their efforts, I was able to successfully recover my stolen funds. The entire process took some time, but the Aspen Recovery Experts dedicated team provided regular updates and kept me informed throughout the process, which gave me a sense of hope and relief during an otherwise stressful time. If you’re ever in a similar situation, I highly recommend reaching out to a trusted recovery team like Aspen Recovery Expertshhh . Their professionalism, knowledge, and expertise were critical in helping me recover my funds and regain control of my crypto assets. Whatsapp : +1 747 231 9036 Telegram : @ prohackerspy Email : [email protected]
03.08.26 20:06 Philip

I was a victim of a crypto theft involving a Pink Drainer, which resulted in the theft of my Wrapped Bitcoin (WBTC) from my Polygon network. The experience was incredibly frustrating and distressing, as I had no idea how to recover my funds. Unfortunately, by the time I noticed the theft, the funds had already been drained to an address that I had no control over, making it seem like an irreversible situation.The attack happened when I clicked on what appeared to be a legitimate link. I didn’t realize at the time that it was a phishing attempt designed to siphon off my private keys and access my wallet. The Pink Drainer, a type of malicious script used by attackers, is specifically designed to exploit such vulnerabilities in crypto wallets. The moment I realized that my WBTC had been drained from my Polygon network. I felt completely helpless, as I didn’t have direct access to the thief's address, and there was no way to reverse the transaction on my own at that point, I started searching for ways to recover my funds, but most resources only offered generic advice that wasn’t practical in this particular case. I quickly realized that if I wanted to have any hope of getting my assets back, I would need professional assistance. After some research, I came across a reliable and trusted recovery team called Aspen Recovery Experts. Their expertise in cryptocurrency recovery, especially in cases like mine, seemed promising.I decided to reach out to Aspen Recovery Experts, and I’m incredibly grateful that I did. Their team of crypto recovery experts was able to help me trace the stolen funds and identify the path the funds took after they left my wallet. Using advanced tools and techniques, they were able to track the transactions on the blockchain, helping me understand where my WBTC had been sent. More importantly, they worked tirelessly to assist me in contacting the necessary parties and even interfaced with blockchain analysts to help facilitate the recovery process.Thanks to their efforts, I was able to successfully recover my stolen funds. The entire process took some time, but the Aspen Recovery Experts dedicated team provided regular updates and kept me informed throughout the process, which gave me a sense of hope and relief during an otherwise stressful time. If you’re ever in a similar situation, I highly recommend reaching out to a trusted recovery team like Aspen Recovery Expertshhh . Their professionalism, knowledge, and expertise were critical in helping me recover my funds and regain control of my crypto assets. Whatsapp : +1 747 231 9036 Telegram : @ prohackerspy Email : [email protected]
04.08.26 11:05 Kisnoles

Excellent analysis, thank you. I was particularly struck by how rigidly the skill sets the order: data processing and form come first, with color coming last. This really cures the habit of "first a pretty palette, then we'll figure it out." A palette validator using OKLCH + color blindness + WCAG is something most chart generators lack. And regarding the boundaries of competence, it's very clear. Where there's a self-checking loop (color), you delegate freely. Where there's a heuristic (form, data interpretation), you remain the final filter. This is a universal principle, not just for /dataviz. By the way, when you look at trading dashboards (including those of decent platforms like ExpertOption), it's immediately clear who thought about readability and who just threw in rainbow lines. Tools like this skill could greatly improve the quality of analytics. Thanks again for the detailed analysis – saved.
04.08.26 12:37 kimberlyhebertt6877

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
04.08.26 12:37 kimberlyhebertt6877

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
06.08.26 08:11 ROMMYHENDERSON344

All you need is to hire an expert to help you accomplish that. If there's any need to spy on your partner's phone. From my experience I lacked evidence to confront my husband on my suspicion on his infidelity, until I came across REALCYBERHACKERS which many commend him of assisting them in their spying mission. So I contacted him and he provided me with access into his phone to view all text messages, call logs, WhatsApp messages and even her location. This evidence helped me move him off my life . I recommend you consult REALCYBERHACKERS AT gmail com or whatsapp +14106350697 if you need access to your partner's phone or any kind of hacking, they carry out all kinds of hacking job
06.08.26 13:56 lydiassmith567

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06.08.26 13:56 lydiassmith567

HIRE A HACKER YOUR STOLEN CRYPTO RECOVERY / BTC / USDT / ETH WITH THE HELP OF CAPITAL CRYPTO RECOVER. I want to share my experience publicly regarding cryptocurrency wallet recovery, I highly recommend you to contact CAPITAL CRYPTO RECOVER, a professional private investigator in the Bitcoin world. They have a certified expert security team specializing in Bitcoin Recovery Services and have helped many people worldwide recover their lost funds. My wife and I were defrauded by an online manipulator posing as an experienced crypto investment professional. We lost $9.2 Million Stolen BTC in cryptocurrency and were left feeling homeless. After spending hours searching for a reliable crypto recovery service, I discovered CAPITAL CRYPTO RECOVER online. By patiently explaining my situation to their team, I was able to recover all my funds. Remarkably, my money was returned to my wallet in less than 24 hours. I am extremely grateful to CAPITAL CRYPTO RECOVER for their excellent assistance—they truly were a godsend in my difficult situation. If you have fallen victim to a cryptocurrency scam, you can reach CAPITAL CRYPTO RECOVER through the following channels Email: [email protected] OR Call/Text: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
11.08.26 03:43 raymont0714

I recommend a trusted cybersecurity PRO with experience in authorized device access, security testing, and data recovery. SHE work only with the owner's consent and follow all legal and privacy rules on meta data. With permission, this specialist can recover lost files, check device security offline & online, and review texts, call records, or hidden data (spy or lurk around a cheating partner or colleuge). Strict confidentiality agreements protect the information, and client details remain private. The work is careful, efficient, and suited to complex cases. For help securing or recovering information from a phone or another electronic device, use the details below 2 consult [email protected] +44 7476618364 I trust her secrecy a living witness. Her discretion is unmatched, ensuring your privacy is always maintained
12.08.26 16:37 rssllhrnsb

I learned an important lesson after investing in what appeared to be a genuine opportunity. Unfortunately, I was unable to access my funds, which reinforced the importance of carrying out thorough due diligence, checking whether an investment is appropriately regulated, and seeking qualified professional advice rather than relying solely on online reviews or testimonials. During the process of addressing my case, I worked with Mrs. Tatiana Sorina , who communicated clearly, provided regular updates, and handled the matter in a professional manner. According to my experience, I have recovered $50,000 so far, while efforts to resolve the remaining balance are still in progress. If you wish to contact her, the details I used are: Mrs. Tatiana Sorina TEXT : (tatianasorina06 at G_Ma IL dot ..c 0 m)…. Before committing money to any investment, take time to verify the legitimacy of the platform, confirm any relevant regulatory authorisations, and avoid investing more than you can comfortably afford to lose.
16.08.26 01:44 Matt Kegan

CapitalNode Analytics. They help to investigate and recover stolen digital assets from fake trading platforms. Great firm i must say.
18.08.26 04:59 marcushenderson624

Bitcoin Recovery Testimonial After falling victim to a cryptocurrency scam group, I lost $354,000 worth of USDT. I thought all hope was lost from the experience of losing my hard-earned money to scammers. I was devastated and believed there was no way to recover my funds. Fortunately, I started searching for help to recover my stolen funds and I came across a lot of testimonials online about Capital Crypto Recovery, an agent who helps in recovery of lost bitcoin funds, I contacted Capital Crypto Recover Service, and with their expertise, they successfully traced and recovered my stolen assets. Their team was professional, kept me updated throughout the process, and demonstrated a deep understanding of blockchain transactions and recovery protocols. They are trusted and very reliable with a 100% successful rate record Recovery bitcoin, I’m grateful for their help and highly recommend their services to anyone seeking assistance with lost crypto. Contact: [email protected] Phone WhatsApp/Text Number: +1 (336) 390-6684 Email: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
18.08.26 04:59 marcushenderson624

Bitcoin Recovery Testimonial After falling victim to a cryptocurrency scam group, I lost $354,000 worth of USDT. I thought all hope was lost from the experience of losing my hard-earned money to scammers. I was devastated and believed there was no way to recover my funds. Fortunately, I started searching for help to recover my stolen funds and I came across a lot of testimonials online about Capital Crypto Recovery, an agent who helps in recovery of lost bitcoin funds, I contacted Capital Crypto Recover Service, and with their expertise, they successfully traced and recovered my stolen assets. Their team was professional, kept me updated throughout the process, and demonstrated a deep understanding of blockchain transactions and recovery protocols. They are trusted and very reliable with a 100% successful rate record Recovery bitcoin, I’m grateful for their help and highly recommend their services to anyone seeking assistance with lost crypto. Contact: [email protected] Phone WhatsApp/Text Number: +1 (336) 390-6684 Email: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
19.08.26 14:50 BAYER7043

My account was locked, and I couldn’t access my own information until [email protected] +447476618364 whats?up? helped me recover it. This lady hacker was kind and professional, but this experience showed me how risky account lockouts can be. If you’re facing the same problem, do not panic consult her A. S. A. P. Be careful with recovery agents outchea, and research their name, business, and reviews before sharing any details. Never send passwords, security codes, banking information, or copies of your ID unless you’ve confirmed who you’re dealing with. Be wary of promises that sound too good to be true, especially claims that require little information or guarantee instant access with outrageous fees.
20.08.26 11:32 michaeldavenport218

I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance contact [email protected] and on Telegram OR WhatsApp Number +1 (336)390-6684 via email: [email protected] you can visit his website: https://recovercapital.wixsite.com/capital-crypto-rec-1
20.08.26 11:32 michaeldavenport218

I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance contact [email protected] and on Telegram OR WhatsApp Number +1 (336)390-6684 via email: [email protected] you can visit his website: https://recovercapital.wixsite.com/capital-crypto-rec-1
23.08.26 20:02 leslieyee

Excellent analysis by /dataviz! I was particularly struck by how strictly the order is defined: "data meaning first, color last" and how the validator actually adjusts the palette according to OKLCH, color blindness, and WCAG standards. These rules greatly improve the quality of charts. By the way, a similar approach to clean and legible charts is highly valued in trading—for example, on the ExpertOption platform, the interface and price visualization are designed to ensure information is read instantly and without unnecessary noise.
25.08.26 13:44 lydiassmith567

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25.08.26 13:44 lydiassmith567

HIRE A HACKER YOUR STOLEN CRYPTO RECOVERY / BTC / USDT / ETH WITH THE HELP OF CAPITAL CRYPTO RECOVER. I want to share my experience publicly regarding cryptocurrency wallet recovery, I highly recommend you to contact CAPITAL CRYPTO RECOVER, a professional private investigator in the Bitcoin world. They have a certified expert security team specializing in Bitcoin Recovery Services and have helped many people worldwide recover their lost funds. My wife and I were defrauded by an online manipulator posing as an experienced crypto investment professional. We lost $9.2 Million Stolen BTC in cryptocurrency and were left feeling homeless. After spending hours searching for a reliable crypto recovery service, I discovered CAPITAL CRYPTO RECOVER online. By patiently explaining my situation to their team, I was able to recover all my funds. Remarkably, my money was returned to my wallet in less than 24 hours. I am extremely grateful to CAPITAL CRYPTO RECOVER for their excellent assistance—they truly were a godsend in my difficult situation. If you have fallen victim to a cryptocurrency scam, you can reach CAPITAL CRYPTO RECOVER through the following channels Email: [email protected] OR Call/WhatsApp: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
30.08.26 15:37 [email protected]

Discovering I had been defrauded, I searched online for services claiming to recover stolen ETH. I contacted several companies, but none succeeded. Although some claimed they could trace assets or recover funds, I could not verify their success or recover my money. I later found SYLVESTER BRYANT Recovery through Google. After contacting him, he recovered 450,000,00. He can be reached at [email protected] or WhatsApp at +1 512 577 7957.
30.08.26 15:37 [email protected]

Discovering I had been defrauded, I searched online for services claiming to recover stolen ETH. I contacted several companies, but none succeeded. Although some claimed they could trace assets or recover funds, I could not verify their success or recover my money. I later found SYLVESTER BRYANT Recovery through Google. After contacting him, he recovered 450,000,00. He can be reached at [email protected] or WhatsApp at +1 512 577 7957.
01.09.26 11:16 lisawerth897

My Experience With Cryptocurrency — CAPITAL CRYPTO RECOVER I lost over $82,000 in Bitcoin after falling victim to a fraudulent online investment scheme. After realizing I had been scammed, I spent considerable time researching possible ways to recover my funds. During my research, I came across CAPITAL CRYPTO RECOVER and decided to contact them after reading their reported success record and encouraging client positive reviews and testimonials. Their team guided me through the recovery process, and I was grateful to successfully recover my lost cryptocurrency. The experience was challenging, but I appreciated the assistance and support I received throughout the process. I’m sharing my experience in the hope that it may encourage other victims to carefully research their options and verify any recovery service before proceeding. I will forever be thankful to you CAPITAL CRYPTO RECOVER 📧 [email protected] 🌐 Website: recovercapital.wixsite.com/capital-crypto-rec-1 📧 [email protected] 📞 Call/WhatsApp: +1 (336) 390-6684
01.09.26 11:16 lisawerth897

My Experience With Cryptocurrency — CAPITAL CRYPTO RECOVER I lost over $82,000 in Bitcoin after falling victim to a fraudulent online investment scheme. After realizing I had been scammed, I spent considerable time researching possible ways to recover my funds. During my research, I came across CAPITAL CRYPTO RECOVER and decided to contact them after reading their reported success record and encouraging client positive reviews and testimonials. Their team guided me through the recovery process, and I was grateful to successfully recover my lost cryptocurrency. The experience was challenging, but I appreciated the assistance and support I received throughout the process. I’m sharing my experience in the hope that it may encourage other victims to carefully research their options and verify any recovery service before proceeding. I will forever be thankful to you CAPITAL CRYPTO RECOVER 📧 [email protected] 🌐 Website: recovercapital.wixsite.com/capital-crypto-rec-1 📧 [email protected] 📞 Call/WhatsApp: +1 (336) 390-6684
01.09.26 17:34 Garry42

Really crazy world. These fraudsters go at any length to steal your hard earned funds. I have been a victim of a bitcoin scam about 7 months back. A Con artist gained access to my cashapp account through a phishing scam. They stole $409,000. I was really devastated. I did everything to get back my funds by contacting the FBI but they claimed there was nothing they could do. A friend told me about a recovery expert. He helps fight against various phishing and investment scams and they were able to help trace and recover my funds even though it took over 2 days. you can reach out to him through recoverydarek@gmail. com . I can guarantee his services are still active.
01.09.26 17:34 Garry42

Really crazy world. These fraudsters go at any length to steal your hard earned funds. I have been a victim of a bitcoin scam about 7 months back. A Con artist gained access to my cashapp account through a phishing scam. They stole $409,000. I was really devastated. I did everything to get back my funds by contacting the FBI but they claimed there was nothing they could do. A friend told me about a recovery expert. He helps fight against various phishing and investment scams and they were able to help trace and recover my funds even though it took over 2 days. you can reach out to him through recoverydarek@gmail. com . I can guarantee his services are still active.
02.09.26 03:43 kimberlyhebertt6877

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] WhatsApp/Text Number: +1 (336) 390-6684
02.09.26 03:43 kimberlyhebertt6877

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] WhatsApp/Text Number: +1 (336) 390-6684
04.09.26 21:51 Kovengray

Recovering your lost investment funds as the case might be, is not what you can do alone, you’d require the service of a trained recovery specialist. A recovery specialist is a person or a group of people who are well equipped to work around the brokerage network. They have vast knowledge about the whole network and have the right software and private keys to follow any transaction. I was ripped off trading online to an investment broker, good thing I got every penny back through the help of Gavin ray he’s a genius Contact : Gavinray78 at gmail com or WhatsApp +1 352 322 2096 It is also important to be patient and really calm during the process.
05.09.26 21:38 [email protected]

I invested 45,000 Euro, and later aggreviated to 198,000 Euro. I requested to place ‎Withdrawal of my funds to be paid to my Bank account. But nothing happened I was subjected to pay more fee until I can get my funds on my account, i got in touch with Theodore ryan here on this platform who had helped a lot of people, I followed all instructions and he legally got back my withheld funds, I got threatened by the company that if I don’t pay they will get my account frozen, all thanks to Theodore ryan and I highly recommend him to anyone dealing with an unregulated broker company… contact him on his Gmail - theodoreryan318@ gmail . com
09.09.26 21:31 lisawerth897

My Experience With Cryptocurrency — CAPITAL CRYPTO RECOVER I lost over $82,000 in Bitcoin after falling victim to a fraudulent online investment scheme. After realizing I had been scammed, I spent considerable time researching possible ways to recover my funds. During my research, I came across CAPITAL CRYPTO RECOVER and decided to contact them after reading their reported success record and encouraging client positive reviews and testimonials. Their team guided me through the recovery process, and I was grateful to successfully recover my lost cryptocurrency. The experience was challenging, but I appreciated the assistance and support I received throughout the process. I’m sharing my experience in the hope that it may encourage other victims to carefully research their options and verify any recovery service before proceeding. I will forever be thankful to you CAPITAL CRYPTO RECOVER 📧 [email protected] 🌐 Website: recovercapital.wixsite.com/capital-crypto-rec-1 📧 [email protected] 📞 Call/WhatsApp: +1 (336) 390-6684
09.09.26 21:31 lisawerth897

My Experience With Cryptocurrency — CAPITAL CRYPTO RECOVER I lost over $82,000 in Bitcoin after falling victim to a fraudulent online investment scheme. After realizing I had been scammed, I spent considerable time researching possible ways to recover my funds. During my research, I came across CAPITAL CRYPTO RECOVER and decided to contact them after reading their reported success record and encouraging client positive reviews and testimonials. Their team guided me through the recovery process, and I was grateful to successfully recover my lost cryptocurrency. The experience was challenging, but I appreciated the assistance and support I received throughout the process. I’m sharing my experience in the hope that it may encourage other victims to carefully research their options and verify any recovery service before proceeding. I will forever be thankful to you CAPITAL CRYPTO RECOVER 📧 [email protected] 🌐 Website: recovercapital.wixsite.com/capital-crypto-rec-1 📧 [email protected] 📞 Call/WhatsApp: +1 (336) 390-6684
09.09.26 23:22 Fraddy Pual

Hearing that these individuals are focusing on other people makes me very sad. I had a similar situation with them and lost a lot of money, but after learning about (Cruxcipherteam @ proton DoT me), whataqq:+168160-15021, telegram: @Cruxcipherteam I was able to get my money back. It's critical that we all be watchful and keep reporting these occurrences.
11.09.26 03:23 kimberlyhebertt6877

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] WhatsApp/Text Number: +1 (336) 390-6684
11.09.26 03:23 kimberlyhebertt6877

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] WhatsApp/Text Number: +1 (336) 390-6684
15.09.26 03:35 elioduncan

I fell victim to a freelance web development contract scam that ultimately cost me CAD 4,000. It all started when I came across a job posting on Indeed Canada, a popular online job portal. The position seemed perfect: a freelance web developer role for an established company looking for someone to design and build a fully functional e-commerce website. The job promised a high payment of CAD 20,000 upon successful completion, which sounded like a great opportunity for me to gain experience and earn decent pay.The employer, who introduced himself as a project manager from a "well-known" tech company, was very persuasive and professional in our initial communication. He explained that the project involved developing a user-friendly, responsive online store for their client and that they had a strict timeline to meet. He assured me that the payment would be made promptly after completing the tasks. However, before starting the work, he told me that I would need to pay an upfront fee of CAD 4,000 to cover certain software tools and licensing fees required for the project. This was supposedly a part of their company policy for freelance contractors, ensuring access to their premium resources. The idea of working on a professional project, coupled with the promise of a substantial payout, convinced me to pay the upfront fee.As soon as I made the payment, the project manager became increasingly difficult to reach. He initially responded to my emails and provided some vague instructions on what the project would entail, but as time went on, communication slowed to a complete halt. I never received the required tools or any proper project details. My emails went unanswered, and any attempts to contact the company were met with silence. After waiting for weeks, I realized that I had been scammed.Desperate to recover my money, I turned to TechY Force Cyber Retrieval, a service that specializes in helping victims of online scams. They helped me track the payment and took legal steps to pursue the fraudsters. Through their guidance, I was able to recover the full CAD 4,000. TechY Force Cyber Retrieval worked with my bank to reverse the transaction and liaised with the authorities to trace the scammer's details.This was a hard lesson, and I now know to be highly cautious about online job offers that require upfront payments. It is crucial to research companies thoroughly and avoid any job that seems too good to be true, especially when it involves paying money upfront. WhatsApp https://wa.link/2x6ktp Mail. [email protected]
15.09.26 15:45 lydiassmith567

HIRE A HACKER YOUR STOLEN CRYPTO RECOVERY / BTC / USDT / ETH WITH THE HELP OF CAPITAL CRYPTO RECOVER. I want to share my experience publicly regarding cryptocurrency wallet recovery, I highly recommend you to contact CAPITAL CRYPTO RECOVER, a professional private investigator in the Bitcoin world. They have a certified expert security team specializing in Bitcoin Recovery Services and have helped many people worldwide recover their lost funds. My wife and I were defrauded by an online manipulator posing as an experienced crypto investment professional. We lost $9.2 Million Stolen BTC in cryptocurrency and were left feeling homeless. After spending hours searching for a reliable crypto recovery service, I discovered CAPITAL CRYPTO RECOVER online. By patiently explaining my situation to their team, I was able to recover all my funds. Remarkably, my money was returned to my wallet in less than 24 hours. I am extremely grateful to CAPITAL CRYPTO RECOVER for their excellent assistance—they truly were a godsend in my difficult situation. If you have fallen victim to a cryptocurrency scam, you can reach CAPITAL CRYPTO RECOVER through the following channels Email: [email protected] OR Call/WhatsApp: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
15.09.26 15:45 lydiassmith567

HIRE A HACKER YOUR STOLEN CRYPTO RECOVERY / BTC / USDT / ETH WITH THE HELP OF CAPITAL CRYPTO RECOVER. I want to share my experience publicly regarding cryptocurrency wallet recovery, I highly recommend you to contact CAPITAL CRYPTO RECOVER, a professional private investigator in the Bitcoin world. They have a certified expert security team specializing in Bitcoin Recovery Services and have helped many people worldwide recover their lost funds. My wife and I were defrauded by an online manipulator posing as an experienced crypto investment professional. We lost $9.2 Million Stolen BTC in cryptocurrency and were left feeling homeless. After spending hours searching for a reliable crypto recovery service, I discovered CAPITAL CRYPTO RECOVER online. By patiently explaining my situation to their team, I was able to recover all my funds. Remarkably, my money was returned to my wallet in less than 24 hours. I am extremely grateful to CAPITAL CRYPTO RECOVER for their excellent assistance—they truly were a godsend in my difficult situation. If you have fallen victim to a cryptocurrency scam, you can reach CAPITAL CRYPTO RECOVER through the following channels Email: [email protected] OR Call/WhatsApp: +1 (336) 390-6684 Contact: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1