Methods › Audio › Speech Recognition › wav2vec-U
wav2vec Unsupervised
wav2vec-U
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
wav2vec-U is an unsupervised method to train speech recognition models without any labeled data. It leverages self-supervised speech representations to segment unlabeled language and learn a mapping from these representations to phonemes via adversarial training.
Specifically, we learn self-supervised representations with wav2vec 2.0 on unlabeled speech audio, then identify clusters in the representations with k-means to segment the audio data. Next, we build segment representations by mean pooling the wav2vec 2.0 representations, performing PCA and a second mean pooling step between adjacent segments. This is input to the generator which outputs a phoneme sequence that is fed to the discriminator, similar to phonemized unlabeled text to perform adversarial training.
Papers archive 2025-07-28
6 shown of 6, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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The Hidden Dance of Phonemes and Visage: Unveiling the Enigmatic Link between Phonemes and Facial Features 26 Jul 2023 · 1 repository · arXiv:2307.13953
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Unsupervised ASR via Cross-Lingual Pseudo-Labeling 19 May 2023 · 0 repositories · arXiv:2305.13330
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Enhancing Unsupervised Speech Recognition with Diffusion GANs 23 Mar 2023 · 0 repositories · arXiv:2303.13559
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Towards End-to-end Unsupervised Speech Recognition 5 Apr 2022 · 1 repository · arXiv:2204.02492
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Analyzing the Robustness of Unsupervised Speech Recognition 7 Oct 2021 · 0 repositories · arXiv:2110.03509
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Unsupervised Speech Recognition 24 May 2021 · 4 repositories · arXiv:2105.11084Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
Tasks archive 2025-07-28
8 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Speech Recognition | 5 |
| speech-recognition | 5 |
| Unsupervised Speech Recognition | 4 |
| Automatic Speech Recognition | 3 |
| Automatic Speech Recognition (ASR) | 3 |
| Generative Adversarial Network | 1 |
| Language Modeling | 1 |
| Language Modelling | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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