38 citations · 41 across the 28 of their papers we have counts for
28 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-…
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…
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…
Towards Effective and Efficient Non-autoregressive decoders for Conformer and LLM-based ASR using Block-based Attention Mask
Tianzi Wang, Xurong Xie, Zengrui Jin +9
Automatic speech recognition (ASR) systems often rely on autoregressive (AR) Transformer decoder architectures, which limit efficient inference parallelization due to their sequent…
CLEAR: Continuous Latent Autoregressive Modeling for High-quality and Low-latency Speech Synthesis
Chun Yat Wu, Jiajun Deng, Guinan Li +2
Autoregressive (AR) language models have emerged as powerful solutions for zero-shot text-to-speech (TTS) synthesis, capable of generating natural speech from a few seconds of audi…
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…
Regularized Federated Learning for Privacy-Preserving Dysarthric and Elderly Speech Recognition
Tao Zhong, Mengzhe Geng, Shujie Hu +2
Accurate recognition of dysarthric and elderly speech remains challenging to date. While privacy concerns have driven a shift from centralized approaches to federated learning (FL)…
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…
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…
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…
Structured Speaker-Deficiency Adaptation of Foundation Models for Dysarthric and Elderly Speech Recognition
Shujie Hu, Xurong Xie, Mengzhe Geng +8
Data-intensive fine-tuning of speech foundation models (SFMs) to scarce and diverse dysarthric and elderly speech leads to data bias and poor generalization to unseen speakers. Thi…
Homogeneous Speaker Features for On-the-Fly Dysarthric and Elderly Speaker Adaptation
Mengzhe Geng, Xurong Xie, Jiajun Deng +7
The application of data-intensive automatic speech recognition (ASR) technologies to dysarthric and elderly adult speech is confronted by their mismatch against healthy and nonaged…
Self-supervised ASR Models and Features For Dysarthric and Elderly Speech Recognition
Shujie Hu, Xurong Xie, Mengzhe Geng +8
Self-supervised learning (SSL) based speech foundation models have been applied to a wide range of ASR tasks. However, their application to dysarthric and elderly speech via data-i…
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…
Towards Effective and Efficient Non-autoregressive Decoding Using Block-based Attention Mask
Tianzi Wang, Xurong Xie, Zhaoqing Li +9
This paper proposes a novel non-autoregressive (NAR) block-based Attention Mask Decoder (AMD) that flexibly balances performance-efficiency trade-offs for Conformer ASR systems. AM…
Enhancing Pre-trained ASR System Fine-tuning for Dysarthric Speech Recognition using Adversarial Data Augmentation
Huimeng Wang, Zengrui Jin, Mengzhe Geng +5
Automatic recognition of dysarthric speech remains a highly challenging task to date. Neuro-motor conditions and co-occurring physical disabilities create difficulty in large-scale…
Towards Automatic Data Augmentation for Disordered Speech Recognition
Zengrui Jin, Xurong Xie, Tianzi Wang +5
Automatic recognition of disordered speech remains a highly challenging task to date due to data scarcity. This paper presents a reinforcement learning (RL) based on-the-fly data a…
Audio-visual End-to-end Multi-channel Speech Separation, Dereverberation and Recognition
Guinan Li, Jiajun Deng, Mengzhe Geng +6
Accurate recognition of cocktail party speech containing overlapping speakers, noise and reverberation remains a highly challenging task to date. Motivated by the invariance of vis…
Factorised Speaker-environment Adaptive Training of Conformer Speech Recognition Systems
Jiajun Deng, Guinan Li, Xurong Xie +6
Rich sources of variability in natural speech present significant challenges to current data intensive speech recognition technologies. To model both speaker and environment level…
Use of Speech Impairment Severity for Dysarthric Speech Recognition
Mengzhe Geng, Zengrui Jin, Tianzi Wang +7
A key challenge in dysarthric speech recognition is the speaker-level diversity attributed to both speaker-identity associated factors such as gender, and speech impairment severit…
Confidence Score Based Speaker Adaptation of Conformer Speech Recognition Systems
Jiajun Deng, Xurong Xie, Tianzi Wang +6
Speaker adaptation techniques provide a powerful solution to customise automatic speech recognition (ASR) systems for individual users. Practical application of unsupervised model-…
Adversarial Data Augmentation Using VAE-GAN for Disordered Speech Recognition
Zengrui Jin, Xurong Xie, Mengzhe Geng +5
Automatic recognition of disordered speech remains a highly challenging task to date. The underlying neuro-motor conditions, often compounded with co-occurring physical disabilitie…