Pronunciation-aware unique character encoding for RNN Transducer-based Mandarin speech recognition. (arXiv:2207.14578v1 [cs.CL])

For Mandarin end-to-end (E2E) automatic speech recognition (ASR) tasks,
compared to character-based modeling units, pronunciation-based modeling units
could improve the sharing of modeling units in model training but meet
homophone problems. In this study, we propose to use a novel
pronunciation-aware unique character encoding for building E2E RNN-T-based
Mandarin ASR systems. The proposed encoding is a combination of
pronunciation-base syllable and character index (CI). By introducing the CI,
the RNN-T model can overcome the homophone problem while utilizing the
pronunciation …

arxiv encoding rnn speech speech recognition