HarunoriKawano/Wav2vec2.0
Implementation of the paper "wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations" in Pytorch.
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.
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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.
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57
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9
Language
Python
License
Apache-2.0
Category
Last pushed
May 19, 2023
Commits (30d)
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