HarunoriKawano/Wav2vec2.0

Implementation of the paper "wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations" in Pytorch.

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Emerging

This project helps machine learning engineers and researchers explore speech data without requiring extensive labeled datasets. It takes raw audio recordings and processes them to extract meaningful speech features, which can then be used for various downstream speech tasks. The output is a representation of speech that captures its underlying patterns, useful for training speech recognition or speaker verification models. This is ideal for those working with speech technology.

No commits in the last 6 months.

Use this if you are a machine learning engineer or researcher developing new speech processing models and want to leverage self-supervised learning for speech representations.

Not ideal if you are looking for an out-of-the-box speech-to-text application or a pre-trained model ready for immediate deployment.

speech-recognition audio-analysis deep-learning-research natural-language-processing machine-learning-engineering
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 15 / 25

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Stars

57

Forks

9

Language

Python

License

Apache-2.0

Last pushed

May 19, 2023

Commits (30d)

0

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