**Wav2Vec2** is an open-source deep learning framework developed by Facebook/Meta AI for **automatic speech recognition (ASR)**. It leverages self-supervised learning to convert raw audio into text, enabling developers and researchers to build accurate and efficient speech-to-text pipelines for multiple languages and domains.

Features of Wav2Vec2:

Supports pre-training on large amounts of unlabeled audio and fine-tuning on smaller labeled datasets.
Enables end-to-end speech-to-text pipelines with high accuracy and low latency.
Works with Python and PyTorch, supporting both CPU and GPU environments.
Includes pre-trained base models (like `facebook/wav2vec2-base-960h`) for immediate use.
Modular, extensible, and widely used in voice assistants, transcription services, and real-time speech applications.

To check the installed version of Wav2Vec2 in your environment:

 
$ sudo su 
$ sudo apt update
 $ source /opt/wav2vec2/venv/bin/activate
 $ pip show transformers

Disclaimer: Wav2Vec2’s transcription quality depends on the audio quality, language, and fine-tuning. Always refer to the official Hugging Face documentation for the most accurate and up-to-date information.

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Wav2Vec2

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Wav2Vec2

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Wav2Vec2
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