Automatic assessment of articulation disorders using confident unit-based model adaptation

Hung Yu Su, Chun Hsien Wu, Pei Jen Tsai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

This paper presents an approach to automatic assessment on articulation disorders using unsupervised acoustic model adaptation. Prior knowledge is obtained via the phonological analysis of the speech data from 453 articulation disordered children. A confusion matrix of the recognition units for a specific subject is re-estimated based on the prior knowledge and the recognition results to choose the confident units for adaptation. The adapted acoustic models can effectively improve the recognition performance of the disordered speech and thus used for articulation assessment. In the experiments, the proposed unsupervised adaptation method achieved a significant performance improvement of 9.1% for disordered speech on syllable recognition rate. Automatic assessment also shows encouraging consistency to the assessment from the therapist.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages4513-4516
Number of pages4
DOIs
Publication statusPublished - 2008 Sep 16
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 2008 Mar 312008 Apr 4

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
CountryUnited States
CityLas Vegas, NV
Period08-03-3108-04-04

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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