activity
20192024
most citedImproving Mandarin End-to-End Speech Recognition with Word N-gram Language Model

13 citations · 14 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20241 cited

Preference Alignment Improves Language Model-Based TTS

Jinchuan Tian, Chunlei Zhang, Jiatong Shi +4

Recent advancements in text-to-speech (TTS) have shown that language model (LM)-based systems offer competitive performance to their counterparts. Further optimization can be achie…

eess.AS2022

Speaker-Aware Mixture of Mixtures Training for Weakly Supervised Speaker Extraction

Zifeng Zhao, Rongzhi Gu, Dongchao Yang +2

Dominant researches adopt supervised training for speaker extraction, while the scarcity of ideally clean corpus and channel mismatch problem are rarely considered. To this end, we…

cs.CL202213 cited

Improving Mandarin End-to-End Speech Recognition with Word N-gram Language Model

Jinchuan Tian, Jianwei Yu, Chao Weng +2

Despite the rapid progress of end-to-end (E2E) automatic speech recognition (ASR), it has been shown that incorporating external language models (LMs) into the decoding can further…

cs.CL2021

Layer Reduction: Accelerating Conformer-Based Self-Supervised Model via Layer Consistency

Jinchuan Tian, Rongzhi Gu, Helin Wang +1

Transformer-based self-supervised models are trained as feature extractors and have empowered many downstream speech tasks to achieve state-of-the-art performance. However, both th…

cs.CL2019

A Random Gossip BMUF Process for Neural Language Modeling

Yiheng Huang, Jinchuan Tian, Lei Han +4

Neural network language model (NNLM) is an essential component of industrial ASR systems. One important challenge of training an NNLM is to leverage between scaling the learning pr…