28 citations · 29 across the 7 of their papers we have counts for
7 papers
k2SSL: A Faster and Better Framework for Self-Supervised Speech Representation Learning
Yifan Yang, Jianheng Zhuo, Zengrui Jin +9
Self-supervised learning (SSL) has achieved great success in speech-related tasks. While Transformer and Conformer architectures have dominated SSL backbones, encoders like Zipform…
CR-CTC: Consistency regularization on CTC for improved speech recognition
Zengwei Yao, Wei Kang, Xiaoyu Yang +7
Connectionist Temporal Classification (CTC) is a widely used method for automatic speech recognition (ASR), renowned for its simplicity and computational efficiency. However, it of…
LibriheavyMix: A 20,000-Hour Dataset for Single-Channel Reverberant Multi-Talker Speech Separation, ASR and Speaker Diarization
Zengrui Jin, Yifan Yang, Mohan Shi +10
The evolving speech processing landscape is increasingly focused on complex scenarios like meetings or cocktail parties with multiple simultaneous speakers and far-field conditions…
SUBLLM: A Novel Efficient Architecture with Token Sequence Subsampling for LLM
Quandong Wang, Yuxuan Yuan, Xiaoyu Yang +6
While Large Language Models (LLMs) have achieved remarkable success in various fields, the efficiency of training and inference remains a major challenge. To address this issue, we…
Zipformer: A faster and better encoder for automatic speech recognition
Zengwei Yao, Liyong Guo, Xiaoyu Yang +6
The Conformer has become the most popular encoder model for automatic speech recognition (ASR). It adds convolution modules to a transformer to learn both local and global dependen…
Libriheavy: a 50,000 hours ASR corpus with punctuation casing and context
Wei Kang, Xiaoyu Yang, Zengwei Yao +5
In this paper, we introduce Libriheavy, a large-scale ASR corpus consisting of 50,000 hours of read English speech derived from LibriVox. To the best of our knowledge, Libriheavy i…
PromptASR for contextualized ASR with controllable style
Xiaoyu Yang, Wei Kang, Zengwei Yao +5
Prompts are crucial to large language models as they provide context information such as topic or logical relationships. Inspired by this, we propose PromptASR, a framework that in…