7 papers
Self-Improving Large Language Models via Progressive Experience Evolution
Shijie Ren, Xiting Wang, Meng Li +8
Large language models (LLMs) capable of self-improvement require not only effective policy optimization, but also a principled mechanism for transforming transient interaction expe…
H-SAGE: Holistic Speaker-Aware Guided Experts for MoE-based Multi-Talker ASR
Yujie Guo, Jiaming Zhou, Yuhang Jia +2
Multi-talker Automatic Speech Recognition (MTASR) faces significant challenges in accurately transcribing overlapping speech, particularly under complex high-overlap conditions. Wh…
GLAD: Global-Local Aware Dynamic Mixture-of-Experts for Multi-Talker ASR
Yujie Guo, Jiaming Zhou, Yuhang Jia +2
End-to-end multi-talker automatic speech recognition (MTASR) faces significant challenges in accurately transcribing overlapping speech. A critical bottleneck is that speaker-speci…
Towards Automatic Evaluation and High-Quality Pseudo-Parallel Dataset Construction for Audio Editing: A Human-in-the-Loop Method
Yuhang Jia, Hui Wang, Xin Nie +3
Audio editing aims to manipulate audio content based on textual descriptions, supporting tasks such as adding, removing, or replacing audio events. Despite recent progress, the lac…
DIFFA: Large Language Diffusion Models Can Listen and Understand
Jiaming Zhou, Hongjie Chen, Shiwan Zhao +9
Recent advances in large language models (LLMs) have shown remarkable capabilities across textual and multimodal domains. In parallel, diffusion-based language models have emerged…
ChildMandarin: A Comprehensive Mandarin Speech Dataset for Young Children Aged 3-5
Jiaming Zhou, Shiyao Wang, Shiwan Zhao +10
Automatic speech recognition (ASR) systems have advanced significantly with models like Whisper, Conformer, and self-supervised frameworks such as Wav2vec 2.0 and HuBERT. However,…