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fix model link (#2408)
Summary: # Before submitting - [ ] Was this discussed/approved via a Github issue? (no need for typos, doc improvements) - [ ] Did you read the [contributor guideline](https://github.com/pytorch/fairseq/blob/main/CONTRIBUTING.md)? - [ ] Did you make sure to update the docs? - [ ] Did you write any new necessary tests? ## What does this PR do? Fixes # (issue). ## PR review Anyone in the community is free to review the PR once the tests have passed. If we didn't discuss your PR in Github issues there's a high chance it will not be merged. ## Did you have fun? Make sure you had fun coding � Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/2408 Reviewed By: alexeib Differential Revision: D31422844 Pulled By: xuqiantong fbshipit-source-id: 348050118621de922c08632ca7f31dedba109da1
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@ -55,7 +55,7 @@ We also finetuned XLSR-53 on languages from [CommonVoice](https://commonvoice.mo
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Pretrained Model | Fintune Dataset | # Languages | Phonemizer | Model | Dictionary
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XLSR-53 | CommonVoice | 26 | [Espeak](https://github.com/espeak-ng/espeak-ng/blob/master/docs/languages.md) | [download](https://dl.fbaipublicfiles.com/fairseq/zero_shot/espeak_26lang_m10.pt) | [download](https://dl.fbaipublicfiles.com/fairseq/wav2vec/zero_shot/espeak_dict.txt)
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XLSR-53 | CommonVoice | 26 | [Espeak](https://github.com/espeak-ng/espeak-ng/blob/master/docs/languages.md) | [download](https://dl.fbaipublicfiles.com/fairseq/wav2vec/zero_shot/espeak_26lang_m10.pt) | [download](https://dl.fbaipublicfiles.com/fairseq/wav2vec/zero_shot/espeak_dict.txt)
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XLSR-53 | CommonVoice | 21 | [Phonetisaurus](https://github.com/AdolfVonKleist/Phonetisaurus) | [download](https://dl.fbaipublicfiles.com/fairseq/wav2vec/zero_shot/phonetisaurus_21lang_m10.pt) | [download](https://dl.fbaipublicfiles.com/fairseq/wav2vec/zero_shot/phonetisaurus_dict.txt)
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We release 2 models that are finetuned on data from 2 different phonemizers. Although the phonemes are all [IPA](https://en.wikipedia.org/wiki/International_Phonetic_Alphabet) symbols, there are still subtle differences between the phonemized transcriptions from the 2 phonemizers. Thus, it's better to use the corresponding model, if your data is phonemized by either phonemizer above.
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