4 citations · 4 across the 4 of their papers we have counts for
4 papers
Phoneme-based speech recognition driven by large language models and sampling marginalization
Te Ma, Nanjie Li, Hao Huang +1
Recently, the Large Language Model-based Phoneme-to-Grapheme (LLM-P2G) method has shown excellent performance in speech recognition tasks and has become a feasible direction to rep…
Pronunciation-Lexicon Free Training for Phoneme-based Crosslingual ASR via Joint Stochastic Approximation
Saierdaer Yusuyin, Te Ma, Hao Huang +1
Recently, pre-trained models with phonetic supervision have demonstrated their advantages for crosslingual speech recognition in data efficiency and information sharing across lang…
LLM-based phoneme-to-grapheme for phoneme-based speech recognition
Te Ma, Min Bi, Saierdaer Yusuyin +2
In automatic speech recognition (ASR), phoneme-based multilingual pre-training and crosslingual fine-tuning is attractive for its high data efficiency and competitive results compa…
Whistle: Data-Efficient Multilingual and Crosslingual Speech Recognition via Weakly Phonetic Supervision
Saierdaer Yusuyin, Te Ma, Hao Huang +2
There exist three approaches for multilingual and crosslingual automatic speech recognition (MCL-ASR) - supervised pretraining with phonetic or graphemic transcription, and self-su…