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Thai Wav2Vec2 with CommonVoice V8 (deepcut tokenizer) + language model

This model trained with CommonVoice V8 dataset by increase data from CommonVoice V7 dataset that It was use in airesearch/wav2vec2-large-xlsr-53-th. It was finetune wav2vec2-large-xlsr-53.

Model description


It is increase new data from The Common Voice V8 dataset to Common Voice V7 dataset or remove all data in Common Voice V7 dataset before split Common Voice V8 then add CommonVoice V7 dataset back to dataset.

It use ekapolc/Thai_commonvoice_split script for split Common Voice dataset.


This model was finetune wav2vec2-large-xlsr-53 model with Thai Common Voice V8 dataset and It use pre-tokenize with deepcut.tokenize.


Test with CommonVoice V8 Testset

Model WER by newmm (%) WER by deepcut (%) CER
AIResearch.in.th and PyThaiNLP 17.414503 11.923089 3.854153
wav2vec2 with deepcut 16.354521 11.424476 3.684060
wav2vec2 with newmm 16.698299 11.436941 3.737407
wav2vec2 with deepcut + language model 12.630260 9.613886 3.292073
wav2vec2 with newmm + language model 12.583706 9.598305 3.276610

Test with CommonVoice V7 Testset (same test by CV V7)

Model WER by newmm (%) WER by deepcut (%) CER
AIResearch.in.th and PyThaiNLP 13.936698 9.347462 2.804787
wav2vec2 with deepcut 12.776381 8.773006 2.628882
wav2vec2 with newmm 12.750596 8.672616 2.623341
wav2vec2 with deepcut + language model 9.940050 7.423313 2.344940
wav2vec2 with newmm + language model 9.559724 7.339654 2.277071

This is use same testset from https://huggingface.co/airesearch/wav2vec2-large-xlsr-53-th.


BibTeX entry and citation info

      title={Thai Wav2Vec2.0 with CommonVoice V8}, 
      author={Wannaphong Phatthiyaphaibun and Chompakorn Chaksangchaichot and Peerat Limkonchotiwat and Ekapol Chuangsuwanich and Sarana Nutanong},
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Dataset used to train wannaphong/wav2vec2-large-xlsr-53-th-cv8-deepcut

Space using wannaphong/wav2vec2-large-xlsr-53-th-cv8-deepcut 1