8 citations · 20 across the 25 of their papers we have counts for
25 papers
DASA: Difficulty-Aware Semantic Augmentation for Speaker Verification
Yuanyuan Wang, Yang Zhang, Zhiyong Wu +4
Data augmentation is vital to the generalization ability and robustness of deep neural networks (DNNs) models. Existing augmentation methods for speaker verification manipulate the…
Text-Only Domain Adaptation for End-to-End Speech Recognition through Down-Sampling Acoustic Representation
Jiaxu Zhu, Weinan Tong, Yaoxun Xu +6
Mapping two modalities, speech and text, into a shared representation space, is a research topic of using text-only data to improve end-to-end automatic speech recognition (ASR) pe…
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…
AV-SepFormer: Cross-Attention SepFormer for Audio-Visual Target Speaker Extraction
Jiuxin Lin, Xinyu Cai, Heinrich Dinkel +7
Visual information can serve as an effective cue for target speaker extraction (TSE) and is vital to improving extraction performance. In this paper, we propose AV-SepFormer, a Sep…
Unified Modeling of Multi-Talker Overlapped Speech Recognition and Diarization with a Sidecar Separator
Lingwei Meng, Jiawen Kang, Mingyu Cui +3
Multi-talker overlapped speech poses a significant challenge for speech recognition and diarization. Recent research indicated that these two tasks are inter-dependent and compleme…
Inter-SubNet: Speech Enhancement with Subband Interaction
Jun Chen, Wei Rao, Zilin Wang +5
Subband-based approaches process subbands in parallel through the model with shared parameters to learn the commonality of local spectrums for noise reduction. In this way, they ha…
Interpretable Unified Language Checking
Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang +7
Despite recent concerns about undesirable behaviors generated by large language models (LLMs), including non-factual, biased, and hateful language, we find LLMs are inherent multi-…
A Hierarchical Regression Chain Framework for Affective Vocal Burst Recognition
Jinchao Li, Xixin Wu, Kaitao Song +3
As a common way of emotion signaling via non-linguistic vocalizations, vocal burst (VB) plays an important role in daily social interaction. Understanding and modeling human vocal…
Leveraging Pretrained Representations with Task-related Keywords for Alzheimer's Disease Detection
Jinchao Li, Kaitao Song, Junan Li +5
With the global population aging rapidly, Alzheimer's disease (AD) is particularly prominent in older adults, which has an insidious onset and leads to a gradual, irreversible dete…
A Sidecar Separator Can Convert a Single-Talker Speech Recognition System to a Multi-Talker One
Lingwei Meng, Jiawen Kang, Mingyu Cui +3
Although automatic speech recognition (ASR) can perform well in common non-overlapping environments, sustaining performance in multi-talker overlapping speech recognition remains c…
Exploring Self-supervised Pre-trained ASR Models For Dysarthric and Elderly Speech Recognition
Shujie Hu, Xurong Xie, Zengrui Jin +6
Automatic recognition of disordered and elderly speech remains a highly challenging task to date due to the difficulty in collecting such data in large quantities. This paper explo…
Speech Enhancement with Fullband-Subband Cross-Attention Network
Jun Chen, Wei Rao, Zilin Wang +5
FullSubNet has shown its promising performance on speech enhancement by utilizing both fullband and subband information. However, the relationship between fullband and subband in F…
Disentangled Speech Representation Learning for One-Shot Cross-lingual Voice Conversion Using -VAE
Hui Lu, Disong Wang, Xixin Wu +3
We propose an unsupervised learning method to disentangle speech into content representation and speaker identity representation. We apply this method to the challenging one-shot c…
Discriminative Speaker Representation via Contrastive Learning with Class-Aware Attention in Angular Space
Zhe Li, Man-Wai Mak, Helen Mei-Ling Meng
The challenges in applying contrastive learning to speaker verification (SV) are that the softmax-based contrastive loss lacks discriminative power and that the hard negative pairs…
Exploiting prompt learning with pre-trained language models for Alzheimer's Disease detection
Yi Wang, Jiajun Deng, Tianzi Wang +4
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating preventive care and to delay further progression. Speech based automatic AD screening systems provide a non-i…
A Multi-Stage Multi-Codebook VQ-VAE Approach to High-Performance Neural TTS
Haohan Guo, Fenglong Xie, Frank K. Soong +2
We propose a Multi-Stage, Multi-Codebook (MSMC) approach to high-performance neural TTS synthesis. A vector-quantized, variational autoencoder (VQ-VAE) based feature analyzer is us…
Bayesian Neural Network Language Modeling for Speech Recognition
Boyang Xue, Shoukang Hu, Junhao Xu +3
State-of-the-art neural network language models (NNLMs) represented by long short term memory recurrent neural networks (LSTM-RNNs) and Transformers are becoming highly complex. Th…
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…
Towards Green ASR: Lossless 4-bit Quantization of a Hybrid TDNN System on the 300-hr Switchboard Corpus
Junhao Xu, Shoukang Hu, Xunying Liu +1
State of the art time automatic speech recognition (ASR) systems are becoming increasingly complex and expensive for practical applications. This paper presents the development of…
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…
Exploring linguistic feature and model combination for speech recognition based automatic AD detection
Yi Wang, Tianzi Wang, Zi Ye +5
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating preventive care and delay progression. Speech based automatic AD screening systems provide a non-intrusive an…
On-the-Fly Feature Based Rapid Speaker Adaptation for Dysarthric and Elderly Speech Recognition
Mengzhe Geng, Xurong Xie, Rongfeng Su +7
Accurate recognition of dysarthric and elderly speech remain challenging tasks to date. Speaker-level heterogeneity attributed to accent or gender, when aggregated with age and spe…