activity
20242026
collaborators

24 papers

cs.SD2026

AudioNoisePrints: Model-free audio watermarking using spatial correlation in flow matching TTS

Timothy Tin-Long, Jian Zhu, Aidan Pine +1

We present AudioNoisePrints, a training-free watermarking pipeline for flow matching and diffusion TTS models, which requires minimal extra computation during inference and does no…

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 Personalized Federated Learning for Dysarthric Speech Recognition

Tao Zhong, Mengzhe Geng, Jiajun Deng +2

Speech recognition is challenging for dysarthric speakers. While federated learning (FL)-based ASR can be an effective tool for protecting privacy, it suffers from heterogeneity is…

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…