Information Retrieval for ZeroSpeech 2021: The Submission by University of Wroclaw
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arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2021
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| _version_ | 1866910600082227200 |
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| author | Chorowski, Jan Ciesielski, Grzegorz Dzikowski, Jarosław Łańcucki, Adrian Marxer, Ricard Opala, Mateusz Pusz, Piotr Rychlikowski, Paweł Stypułkowski, Michał |
| author_facet | Chorowski, Jan Ciesielski, Grzegorz Dzikowski, Jarosław Łańcucki, Adrian Marxer, Ricard Opala, Mateusz Pusz, Piotr Rychlikowski, Paweł Stypułkowski, Michał |
| contents | We present a number of low-resource approaches to the tasks of the Zero Resource Speech Challenge 2021. We build on the unsupervised representations of speech proposed by the organizers as a baseline, derived from CPC and clustered with the k-means algorithm. We demonstrate that simple methods of refining those representations can narrow the gap, or even improve upon the solutions which use a high computational budget. The results lead to the conclusion that the CPC-derived representations are still too noisy for training language models, but stable enough for simpler forms of pattern matching and retrieval. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2106_11603 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Information Retrieval for ZeroSpeech 2021: The Submission by University of Wroclaw Chorowski, Jan Ciesielski, Grzegorz Dzikowski, Jarosław Łańcucki, Adrian Marxer, Ricard Opala, Mateusz Pusz, Piotr Rychlikowski, Paweł Stypułkowski, Michał Machine Learning Sound Audio and Speech Processing We present a number of low-resource approaches to the tasks of the Zero Resource Speech Challenge 2021. We build on the unsupervised representations of speech proposed by the organizers as a baseline, derived from CPC and clustered with the k-means algorithm. We demonstrate that simple methods of refining those representations can narrow the gap, or even improve upon the solutions which use a high computational budget. The results lead to the conclusion that the CPC-derived representations are still too noisy for training language models, but stable enough for simpler forms of pattern matching and retrieval. |
| title | Information Retrieval for ZeroSpeech 2021: The Submission by University of Wroclaw |
| topic | Machine Learning Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2106.11603 |