10 citations · 18 across the 14 of their papers we have counts for
14 papers · 1 filter
A Large-Scale Probing Analysis of Speaker-Specific Attributes in Self-Supervised Speech Representations
Aemon Yat Fei Chiu, Kei Ching Fung, Roger Tsz Yeung Li +2
Enhancing explainability in speech self-supervised learning (SSL) is important for understanding and effectively utilising speech SSL representations. This study conducts a large-s…
An Investigation of Reprogramming for Cross-Language Adaptation in Speaker Verification Systems
Jingyu Li, Aemon Yat Fei Chiu, Tan Lee
Language mismatch is among the most common and challenging domain mismatches in deploying speaker verification (SV) systems. Adversarial reprogramming has shown promising results i…
Creating Personalized Synthetic Voices from Articulation Impaired Speech Using Augmented Reconstruction Loss
Yusheng Tian, Jingyu Li, Tan Lee
This research is about the creation of personalized synthetic voices for head and neck cancer survivors. It is focused particularly on tongue cancer patients whose speech might exh…
Efficient Black-Box Speaker Verification Model Adaptation with Reprogramming and Backend Learning
Jingyu Li, Tan Lee
The development of deep neural networks (DNN) has significantly enhanced the performance of speaker verification (SV) systems in recent years. However, a critical issue that persis…
Convolution-Based Channel-Frequency Attention for Text-Independent Speaker Verification
Jingyu Li, Yusheng Tian, Tan Lee
Deep convolutional neural networks (CNNs) have been applied to extracting speaker embeddings with significant success in speaker verification. Incorporating the attention mechanism…
Model Compression for DNN-based Speaker Verification Using Weight Quantization
Jingyu Li, Wei Liu, Zhaoyang Zhang +2
DNN-based speaker verification (SV) models demonstrate significant performance at relatively high computation costs. Model compression can be applied to reduce the model size for l…
Transport-Oriented Feature Aggregation for Speaker Embedding Learning
Yusheng Tian, Jingyu Li, Tan Lee
Pooling is needed to aggregate frame-level features into utterance-level representations for speaker modeling. Given the success of statistics-based pooling methods, we hypothesize…
Learnable Frequency Filters for Speech Feature Extraction in Speaker Verification
Jingyu Li, Yusheng Tian, Tan Lee
Mel-scale spectrum features are used in various recognition and classification tasks on speech signals. There is no reason to expect that these features are optimal for all differe…
EDITnet: A Lightweight Network for Unsupervised Domain Adaptation in Speaker Verification
Jingyu Li, Wei Liu, Tan Lee
Performance degradation caused by language mismatch is a common problem when applying a speaker verification system on speech data in different languages. This paper proposes a dom…
An Investigation on Applying Acoustic Feature Conversion to ASR of Adult and Child Speech
Wei Liu, Jingyu Li, Tan Lee
The performance of child speech recognition is generally less satisfactory compared to adult speech due to limited amount of training data. Significant performance degradation is e…
Exploiting Pre-Trained ASR Models for Alzheimer's Disease Recognition Through Spontaneous Speech
Ying Qin, Wei Liu, Zhiyuan Peng +4
Alzheimer's disease (AD) is a progressive neurodegenerative disease and recently attracts extensive attention worldwide. Speech technology is considered a promising solution for th…
Improving Text-Independent Speaker Verification with Auxiliary Speakers Using Graph
Jingyu Li, Si-Ioi Ng, Tan Lee
The paper presents a novel approach to refining similarity scores between input utterances for robust speaker verification. Given the embeddings from a pair of input utterances, a…
Detection of Consonant Errors in Disordered Speech Based on Consonant-vowel Segment Embedding
Si-Ioi Ng, Cymie Wing-Yee Ng, Jingyu Li +1
Speech sound disorder (SSD) refers to a type of developmental disorder in young children who encounter persistent difficulties in producing certain speech sounds at the expected ag…
Text-Independent Speaker Verification with Dual Attention Network
Jingyu Li, Tan Lee
This paper presents a novel design of attention model for text-independent speaker verification. The model takes a pair of input utterances and generates an utterance-level embeddi…