collaborators

13 papers

eess.AS2026

Differentiable and Severity-invariant Discrete Tokens for Dysarthric Speech Recognition

Huimeng Wang, Xurong Xie, Mengzhe Geng +5

This paper proposes novel differentiable and severity-invariant (DSI) discrete token approaches that are not only tightly integrated with downstream dysarthric speech recognition t…

eess.AS2026

NormToken: Speaker- and Duration-Normalized Semantic Speech Tokens via Iterative S2U-T2U Refinement

Hanlin Zhang, Daxin Tan, Dehua Tao +3

Semantic speech tokens should preserve linguistic content while suppressing utterance-specific acoustic and duration variation. However, existing speech-to-unit (S2U) tokenizers of…

eess.AS2026

Confidence Score Guided Incremental and Speaker Adaptive Pseudo-Labeling for Semi-Supervised Elderly Speech Recognition

Chengxi Deng, Xurong Xie, Shujie Hu +7

This paper proposes a novel confidence score guided incremental and speaker adaptive pseudo-labeling approach for semi-supervised elderly speech recognition. It facilitates higher-…

eess.AS2026

Decoding while Adapting: Zero-Shot Online Speaker Adaptation via Audio-Textual Prompts for Elderly Speech Recognition

Chengxi Deng, Xurong Xie, Shujie Hu +7

This paper proposes a novel cross-utterance audio-textual prompts based speaker adaptation approach for elderly speech recognition. It enables zero-shot, real-time adaptation to un…

cs.SD2026

Explainable and Trustworthy Speech Emotion Recognition Using Confidence Score and Reinforcement Learning Rectified Speech Emotion Descriptors

Youjun Chen, Xurong Xie, Mengzhe Geng +9

Explainable and trustworthy speech emotion recognition (SER) remains a challenging task to date, largely due to the scarcity of SER data with reliable speech emotion descriptor (SE…

cs.SD2026

Towards Data-free and Training-free Compression for Speech Foundation Models Using Parameter Clustering

Haoning Xu, Zhaoqing Li, Huimeng Wang +4

This paper presents a novel data-free and training-free compression approach for speech foundation models using channelwise clustering via k-means. More fine-grained, mixed sparsit…

gr-qc2026

Reshaping the inner shadow of a Kerr black hole by a torn accretion disk

Shiyang Hu, Dan Li, Chen Deng +1

When an accretion flow extends to the event horizon, their intersection defines the contour of the inner shadow. However, the morphological evolution of this critical feature remai…

cs.SD2026

Multi-Channel Speech Enhancement for Cocktail Party Speech Emotion Recognition

Youjun Chen, Guinan Li, Mengzhe Geng +9

This paper highlights the critical importance of multi-channel speech enhancement (MCSE) for speech emotion recognition (ER) in cocktail party scenarios. A multi-channel speech der…

eess.AS2025

Exploring Cross-Utterance Speech Contexts for Conformer-Transducer Speech Recognition Systems

Mingyu Cui, Mengzhe Geng, Jiajun Deng +8

This paper investigates four types of cross-utterance speech contexts modeling approaches for streaming and non-streaming Conformer-Transformer (C-T) ASR systems: i) input audio fe…

eess.AS2025

MOPSA: Mixture of Prompt-Experts Based Speaker Adaptation for Elderly Speech Recognition

Chengxi Deng, Xurong Xie, Shujie Hu +10

This paper proposes a novel Mixture of Prompt-Experts based Speaker Adaptation approach (MOPSA) for elderly speech recognition. It allows zero-shot, real-time adaptation to unseen…

cs.SD2025

Towards LLM-Empowered Fine-Grained Speech Descriptors for Explainable Emotion Recognition

Youjun Chen, Xurong Xie, Haoning Xu +6

This paper presents a novel end-to-end LLM-empowered explainable speech emotion recognition (SER) approach. Fine-grained speech emotion descriptor (SED) features, e.g., pitch, tone…

cs.SD2025

Effective and Efficient One-pass Compression of Speech Foundation Models Using Sparsity-aware Self-pinching Gates

Haoning Xu, Zhaoqing Li, Youjun Chen +5

This paper presents a novel approach for speech foundation models compression that tightly integrates model pruning and parameter update into a single stage. Highly compact layer-l…

cs.SD2025

On-the-fly Routing for Zero-shot MoE Speaker Adaptation of Speech Foundation Models for Dysarthric Speech Recognition

Shujie HU, Xurong Xie, Mengzhe Geng +8

This paper proposes a novel MoE-based speaker adaptation framework for foundation models based dysarthric speech recognition. This approach enables zero-shot adaptation and real-ti…