Paper Info
Title
DEVELOPMENT OF THE CUHK ELDERLY SPEECH RECOGNITION SYSTEM FOR NEUROCOGNITIVE DISORDER DETECTION USING THE DEMENTIABANK CORPUS
Abstract
Early diagnosis of Neurocognitive Disorder (NCD) is crucial in facilitating preventive care and timely treatment to delay further progression. This paper presents the development of a state-of-the-art automatic speech recognition (ASR) system built on the Dementia-Bank Pitt corpus for automatic NCD detection. Speed perturbation based audio data augmentation expanded the limited elderly speech data by four times. Large quantities of out-of-domain, non-aged adult speech were exploited by cross-domain adapting a 1000-hour LibriSpeech corpus trained LF-MMI factored TDNN system to DementiaBank. The variability among elderly speakers was modeled using i-Vector and learning hidden unit contributions (LHUC) based speaker adaptive training. Robust Bayesian estimation of TDNN systems and LHUC transforms were used in both cross-domain and speaker adaptation. A Transformer language model was also built to improve the final system performance. A word error rate (WER) reduction of 11.72% absolute (26.11% relative) was obtained over the baseline i-Vector adapted LF-MMI TDNN system on the evaluation data of 48 elderly speakers. The best NCD detection accuracy of 88%, comparable to that using the ground truth speech transcripts, was obtained using the textual features extracted from the final ASR system outputs.
Year
DOI
Venue
2021
10.1109/ICASSP39728.2021.9413634
2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)
Keywords
DocType
Citations 
Automatic Speech Recognition, Elderly Speech, Neurocognitive Disorder Detection, Dementia
Conference
0
PageRank 
References 
Authors
0.34
0
11
Name
Order
Citations
PageRank
Zi Ye101.35
Shoukang Hu2610.90
Jinchao Li301.01
Xurong Xie468.57
Mengzhe Geng515.42
Jianwei Yu6810.92
Junhao Xu702.03
Boyang Xue801.01
Shansong Liu925.77
Xunying Liu1033052.46
Helen M. Meng111078172.82