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…
Lightweight and Robust Multi-Channel End-to-End Speech Recognition with Spherical Harmonic Transform
Xiangzhu Kong, Huang Hao, Zhijian Ou
This paper presents SHTNet, a lightweight spherical harmonic transform (SHT) based framework, which is designed to address cross-array generalization challenges in multi-channel au…