216 citations · 227 across the 7 of their papers we have counts for
5 papers · 1 filter
End-to-End Training for Discrete Token LLM based TTS System
Changfeng Gao, Yong Ren, Jun Yuan +3
Recent state-of-the-art (SOTA) text-to-speech (TTS) systems typically adopt a cascaded pipeline consisting of a speech tokenizer, an autoregressive large language model (LLM), and…
Text-Only Domain Adaptation for End-to-End Speech Recognition through Down-Sampling Acoustic Representation
Jiaxu Zhu, Weinan Tong, Yaoxun Xu +6
Mapping two modalities, speech and text, into a shared representation space, is a research topic of using text-only data to improve end-to-end automatic speech recognition (ASR) pe…
3M: Multi-loss, Multi-path and Multi-level Neural Networks for speech recognition
Zhao You, Shulin Feng, Dan Su +1
Recently, Conformer based CTC/AED model has become a mainstream architecture for ASR. In this paper, based on our prior work, we identify and integrate several approaches to achiev…
GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio
Guoguo Chen, Shuzhou Chai, Guanbo Wang +18
This paper introduces GigaSpeech, an evolving, multi-domain English speech recognition corpus with 10,000 hours of high quality labeled audio suitable for supervised training, and…
SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of Experts
Zhao You, Shulin Feng, Dan Su +1
Recently, Mixture of Experts (MoE) based Transformer has shown promising results in many domains. This is largely due to the following advantages of this architecture: firstly, MoE…