93 citations · 114 across the 37 of their papers we have counts for
20 papers · 1 filter
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…
Measuring Prosody Diversity in Zero-Shot TTS: A New Metric, Benchmark, and Exploration
Yifan Yang, Bing Han, Hui Wang +5
Prosody diversity is essential for achieving naturalness and expressiveness in zero-shot text-to-speech (TTS). However, frequently used acoustic metrics capture only partial views…
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…
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…
Disentangling Speakers in Multi-Talker Speech Recognition with Speaker-Aware CTC
Jiawen Kang, Lingwei Meng, Mingyu Cui +4
Multi-talker speech recognition (MTASR) faces unique challenges in disentangling and transcribing overlapping speech. To address these challenges, this paper investigates the role…
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…
GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement
Yifan Yang, Zheshu Song, Jianheng Zhuo +13
The evolution of speech technology has been spurred by the rapid increase in dataset sizes. Traditional speech models generally depend on a large amount of labeled training data, w…
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…
Towards Effective and Compact Contextual Representation for Conformer Transducer Speech Recognition Systems
Mingyu Cui, Jiawen Kang, Jiajun Deng +4
Current ASR systems are mainly trained and evaluated at the utterance level. Long range cross utterance context can be incorporated. A key task is to derive a suitable compact repr…
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-…
Confidence Score Based Conformer Speaker Adaptation for Speech Recognition
Jiajun Deng, Xurong Xie, Tianzi Wang +7
A key challenge for automatic speech recognition (ASR) systems is to model the speaker level variability. In this paper, compact speaker dependent learning hidden unit contribution…
Conformer Based Elderly Speech Recognition System for Alzheimer's Disease Detection
Tianzi Wang, Jiajun Deng, Mengzhe Geng +7
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating preventive care to delay further progression. This paper presents the development of a state-of-the-art Confo…
Two-pass Decoding and Cross-adaptation Based System Combination of End-to-end Conformer and Hybrid TDNN ASR Systems
Mingyu Cui, Jiajun Deng, Shoukang Hu +7
Fundamental modelling differences between hybrid and end-to-end (E2E) automatic speech recognition (ASR) systems create large diversity and complementarity among them. This paper i…
Exploiting Cross-domain And Cross-Lingual Ultrasound Tongue Imaging Features For Elderly And Dysarthric Speech Recognition
Shujie Hu, Xurong Xie, Mengzhe Geng +6
Articulatory features are inherently invariant to acoustic signal distortion and have been successfully incorporated into automatic speech recognition (ASR) systems designed for no…
Exploiting Cross Domain Acoustic-to-articulatory Inverted Features For Disordered Speech Recognition
Shujie Hu, Shansong Liu, Xurong Xie +6
Articulatory features are inherently invariant to acoustic signal distortion and have been successfully incorporated into automatic speech recognition (ASR) systems for normal spee…
Recent Progress in the CUHK Dysarthric Speech Recognition System
Shansong Liu, Mengzhe Geng, Shoukang Hu +5
Despite the rapid progress of automatic speech recognition (ASR) technologies in the past few decades, recognition of disordered speech remains a highly challenging task to date. D…
Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks
Shoukang Hu, Xurong Xie, Mingyu Cui +6
State-of-the-art automatic speech recognition (ASR) system development is data and computation intensive. The optimal design of deep neural networks (DNNs) for these systems often…