10 citations · 18 across the 11 of their papers we have counts for
11 papers
CoMFLP: Correlation Measure based Fast Search on ASR Layer Pruning
Wei Liu, Zhiyuan Peng, Tan Lee
Transformer-based speech recognition (ASR) model with deep layers exhibited significant performance improvement. However, the model is inefficient for deployment on resource-constr…
Sparsely Shared LoRA on Whisper for Child Speech Recognition
Wei Liu, Ying Qin, Zhiyuan Peng +1
Whisper is a powerful automatic speech recognition (ASR) model. Nevertheless, its zero-shot performance on low-resource speech requires further improvement. Child speech, as a repr…
Diffusion-Based Mel-Spectrogram Enhancement for Personalized Speech Synthesis with Found Data
Yusheng Tian, Wei Liu, Tan Lee
Creating synthetic voices with found data is challenging, as real-world recordings often contain various types of audio degradation. One way to address this problem is to pre-enhan…
An ASR-free Fluency Scoring Approach with Self-Supervised Learning
Wei Liu, Kaiqi Fu, Xiaohai Tian +4
A typical fluency scoring system generally relies on an automatic speech recognition (ASR) system to obtain time stamps in input speech for either the subsequent calculation of flu…
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…
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…
A Multi-Resolution Front-End for End-to-End Speech Anti-Spoofing
Wei Liu, Meng Sun, Xiongwei Zhang +2
The choice of an optimal time-frequency resolution is usually a difficult but important step in tasks involving speech signal classification, e.g., speech anti-spoofing. The variat…
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…
Utterance-level neural confidence measure for end-to-end children speech recognition
Wei Liu, Tan Lee
Confidence measure is a performance index of particular importance for automatic speech recognition (ASR) systems deployed in real-world scenarios. In the present study, utterance-…
The CUHK-TUDELFT System for The SLT 2021 Children Speech Recognition Challenge
Si-Ioi Ng, Wei Liu, Zhiyuan Peng +4
This technical report describes our submission to the 2021 SLT Children Speech Recognition Challenge (CSRC) Track 1. Our approach combines the use of a joint CTC-attention end-to-e…