Towards Automatic Assessment Of Aphasia Speech Using Automatic Speech Recognition Techniques
Keywords
Aphasia speech; Automatic speech recognition; Objective assessment
Abstract
Aphasia is a type of acquired language impairment caused by brain injury. This paper presents an automatic speech recognition (ASR) based approach to objective assessment of aphasia patients. A dedicated ASR system is developed to facilitate acoustical and linguistic analysis of Cantonese aphasia speech. The acoustic models and the language models are trained with domain-and style-matched speech data from unimpaired control speakers. The speech recognition performance of this system is evaluated on natural oral discourses from patients with various types of aphasia. We analyze the recognition outputs for a set of selected utterances in the aspects of supra-segmental duration and linguistic content, and confirm the effectiveness of the relevant features in the assessment of aphasia speech.
Publication Date
5-2-2017
Publication Title
Proceedings of 2016 10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ISCSLP.2016.7918445
Copyright Status
Unknown
Socpus ID
85020188141 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85020188141
STARS Citation
Qin, Ying; Lee, Tan; Kong, Anthony Pak Hin; and Law, Sam Po, "Towards Automatic Assessment Of Aphasia Speech Using Automatic Speech Recognition Techniques" (2017). Scopus Export 2015-2019. 6687.
https://stars.library.ucf.edu/scopus2015/6687