1 citations · 1 across the 15 of their papers we have counts for
15 papers
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-…
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…
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…
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…
SemaVoice: Semantic-Aware Continuous Autoregressive Speech Synthesis
Huimeng Wang, Hui Lu, Jiajun Deng +7
Continuous autoregressive speech synthesis has recently emerged as a promising direction for zero-shot text-to-speech (TTS). However, existing methods still suffer from a fundament…
Covo-Audio Technical Report
Wenfu Wang, Chenxing Li, Liqiang Zhang +23
In this work, we present Covo-Audio, a 7B-parameter end-to-end LALM that directly processes continuous audio inputs and generates audio outputs within a single unified architecture…
JAEGER: Joint 3D Audio-Visual Grounding and Reasoning in Simulated Physical Environments
Zhan Liu, Changli Tang, Yuxin Wang +7
Current audio-visual large language models (AV-LLMs) are predominantly restricted to 2D perception, relying on RGB video and monaural audio. This design choice introduces a fundame…
EmotionThinker: Prosody-Aware Reinforcement Learning for Explainable Speech Emotion Reasoning
Dingdong Wang, Shujie Liu, Tianhua Zhang +3
Emotional information in speech plays a unique role in multimodal perception. However, current Speech Large Language Models (SpeechLLMs), similar to conventional speech emotion rec…
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…
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…
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…
Towards One-bit ASR: Extremely Low-bit Conformer Quantization Using Co-training and Stochastic Precision
Zhaoqing Li, Haoning Xu, Zengrui Jin +7
Model compression has become an emerging need as the sizes of modern speech systems rapidly increase. In this paper, we study model weight quantization, which directly reduces the…
Effective and Efficient Mixed Precision Quantization of Speech Foundation Models
Haoning Xu, Zhaoqing Li, Zengrui Jin +7
This paper presents a novel mixed-precision quantization approach for speech foundation models that tightly integrates mixed-precision learning and quantized model parameter estima…
Phone-purity Guided Discrete Tokens for Dysarthric Speech Recognition
Huimeng Wang, Xurong Xie, Mengzhe Geng +6
Discrete tokens extracted provide efficient and domain adaptable speech features. Their application to disordered speech that exhibits articulation imprecision and large mismatch a…
Joint Speaker Features Learning for Audio-visual Multichannel Speech Separation and Recognition
Guinan Li, Jiajun Deng, Youjun Chen +8
This paper proposes joint speaker feature learning methods for zero-shot adaptation of audio-visual multichannel speech separation and recognition systems. xVector and ECAPA-TDNN s…