TTS data augmentation and LLM error correction together cut relative WER by 40-50% on ASR models for oral cancer speech.
Wav2vec 2.0: A framework for self-supervised learning of speech representations,
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Improving Automatic Speech Recognition for Speakers Treated for Oral Cancer using Data Augmentation and LLM Error Correction
TTS data augmentation and LLM error correction together cut relative WER by 40-50% on ASR models for oral cancer speech.