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Recently, Automatic Speech Recognition (ASR), a system that converts audiointo text, has caught a lot of attention in the machine learning community.Thus, a lot of publicly available models were released in HuggingFace. However,most of these ASR models are available in English; only a minority of themodels are available in Thai. Additionally, most of the Thai ASR models areclosed-sourced, and the performance of existing open-sourced models lacksrobustness. To address this problem, we train a new ASR model on a pre-trainedXLSR-Wav2Vec model with the Thai CommonVoice corpus V8 and train a trigramlanguage model to boost the performance of our ASR model. We hope that ourmodels will be beneficial to individuals and the ASR community in Thailand.

Thai Wav2Vec2.0 with CommonVoice V8