activity
20202022
most citedExploiting Pre-Trained ASR Models for Alzheimer's Disease Recognition Through Spontaneous Speech

10 citations · 16 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS20221 cited

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…

cs.SD2021

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…

eess.AS202110 cited

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…

eess.AS20211 cited

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-…

eess.AS20204 cited

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…