TTS data augmentation and LLM error correction together cut relative WER by 40-50% on ASR models for oral cancer speech.
WavLM: Large-Scale Self-Supervised Pre- Training for Full Stack Speech Processing
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.AS 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
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.