38 citations · 47 across the 37 of their papers we have counts for
38 papers
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…
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 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…
IRAF: Interference-Resilient Adaptive Fusion for Noise-Robust End-to-End Full-Duplex Spoken Dialogue Systems
Tao Zhong, Jiajun Deng, Nikita Kuzmin +6
Full-duplex spoken dialogue models allow voice agents to listen and speak concurrently, enabling natural interaction with real-time overlap. However, end-to-end dual-channel models…
UNISON: A Unified Sound Generation and Editing Framework via Deep LLM Fusion
Zhaoqing Li, Haoning Xu, Jingran Su +9
We present UNISON, a latent diffusion framework that unifies speech generation, sound generation, and audio editing within a single model. A single model handles text-to-audio, tex…
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…
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…
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…
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…
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…
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…
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…
Exploring SSL Discrete Speech Features for Zipformer-based Contextual ASR
Mingyu Cui, Yifan Yang, Jiajun Deng +7
Self-supervised learning (SSL) based discrete speech representations are highly compact and domain adaptable. In this paper, SSL discrete speech features extracted from WavLM model…
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…
One-pass Multiple Conformer and Foundation Speech Systems Compression and Quantization Using An All-in-one Neural Model
Zhaoqing Li, Haoning Xu, Tianzi Wang +7
We propose a novel one-pass multiple ASR systems joint compression and quantization approach using an all-in-one neural model. A single compression cycle allows multiple nested sys…
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…
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…
Hyper-parameter Adaptation of Conformer ASR Systems for Elderly and Dysarthric Speech Recognition
Tianzi Wang, Shoukang Hu, Jiajun Deng +5
Automatic recognition of disordered and elderly speech remains highly challenging tasks to date due to data scarcity. Parameter fine-tuning is often used to exploit the large quant…