Automatic Speech Recognition For Acoustical Analysis And Assessment Of Cantonese Pathological Voice And Speech
Keywords
acoustical analysis; automatic speech recognition; objective assessment; Pathological speech
Abstract
This paper describes the application of state-of-the-art automatic speech recognition (ASR) systems to objective assessment of voice and speech disorders. Acoustical analysis of speech has long been considered a promising approach to non-invasive and objective assessment of people. In the past the types and amount of speech materials used for acoustical assessment were very limited. With the ASR technology, we are able to perform acoustical and linguistic analyses with a large amount of natural speech from impaired speakers. The present study is focused on Cantonese, which is a major Chinese dialect. Two representative disorders of speech production are investigated: dysphonia and aphasia. ASR experiments are carried out with continuous and spontaneous speech utterances from Cantonese-speaking patients. The results confirm the feasibility and potential of using natural speech for acoustical assessment of voice and speech disorders, and reveal the challenging issues in acoustic modeling and language modeling of pathological speech.
Publication Date
5-18-2016
Publication Title
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume
2016-May
Number of Pages
6475-6479
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ICASSP.2016.7472924
Copyright Status
Unknown
Socpus ID
84973349172 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84973349172
STARS Citation
Lee, Tan; Liu, Yuanyuan; Huang, Pei Wen; Chien, Jen Tzung; and Lam, Wang Kong, "Automatic Speech Recognition For Acoustical Analysis And Assessment Of Cantonese Pathological Voice And Speech" (2016). Scopus Export 2015-2019. 4506.
https://stars.library.ucf.edu/scopus2015/4506