20 citations · 51 across the 13 of their papers we have counts for
13 papers
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…
Reproducing Whisper-Style Training Using an Open-Source Toolkit and Publicly Available Data
Yifan Peng, Jinchuan Tian, Brian Yan +13
Pre-training speech models on large volumes of data has achieved remarkable success. OpenAI Whisper is a multilingual multitask model trained on 680k hours of supervised speech dat…
AutoPrep: An Automatic Preprocessing Framework for In-the-Wild Speech Data
Jianwei Yu, Hangting Chen, Yanyao Bian +6
Recently, the utilization of extensive open-sourced text data has significantly advanced the performance of text-based large language models (LLMs). However, the use of in-the-wild…
Bayes Risk Transducer: Transducer with Controllable Alignment Prediction
Jinchuan Tian, Jianwei Yu, Hangting Chen +4
Automatic speech recognition (ASR) based on transducers is widely used. In training, a transducer maximizes the summed posteriors of all paths. The path with the highest posterior…
HiFi-Codec: Group-residual Vector quantization for High Fidelity Audio Codec
Dongchao Yang, Songxiang Liu, Rongjie Huang +3
Audio codec models are widely used in audio communication as a crucial technique for compressing audio into discrete representations. Nowadays, audio codec models are increasingly…
Bayes risk CTC: Controllable CTC alignment in Sequence-to-Sequence tasks
Jinchuan Tian, Brian Yan, Jianwei Yu +3
Sequence-to-Sequence (seq2seq) tasks transcribe the input sequence to a target sequence. The Connectionist Temporal Classification (CTC) criterion is widely used in multiple seq2se…
LAE: Language-Aware Encoder for Monolingual and Multilingual ASR
Jinchuan Tian, Jianwei Yu, Chunlei Zhang +3
Despite the rapid progress in automatic speech recognition (ASR) research, recognizing multilingual speech using a unified ASR system remains highly challenging. Previous works on…
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…
Integrating Lattice-Free MMI into End-to-End Speech Recognition
Jinchuan Tian, Jianwei Yu, Chao Weng +2
In automatic speech recognition (ASR) research, discriminative criteria have achieved superior performance in DNN-HMM systems. Given this success, the adoption of discriminative cr…
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…
Consistent Training and Decoding For End-to-end Speech Recognition Using Lattice-free MMI
Jinchuan Tian, Jianwei Yu, Chao Weng +4
Recently, End-to-End (E2E) frameworks have achieved remarkable results on various Automatic Speech Recognition (ASR) tasks. However, Lattice-Free Maximum Mutual Information (LF-MMI…
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…
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…