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Automated screening of speech development issues in children by identifying phonological error patterns

conference contribution
posted on 2023-05-23, 12:09 authored by Ward, L, Stefani, A, Smith, D, Duenser, A, Freyne, J, Dodd, B, Morgan, A
A proof of concept system is developed to provide a broad assessment of speech development issues in children. It has been designed to enable non-experts to complete an initial screening of children's speech with the aim of reducing the workload on Speech Language Pathology services. The system was composed of an acoustic model trained by neural networks with split temporal context features and a constrained HMM-encoded with the knowledge of Speech Language Pathologists. Results demonstrated the system was able to improve PER by 33% compared with standard HMM decoders, with a minimum PER of 19.03% achieved. Identification of Phonological Error Patterns with up to 94% accuracy was achieved despite utilizing only a small corpus of disordered speech from Australian children. These results indicate the proposed system is viable and the direction of further development are outlined in the paper.

History

Publication title

Proceedings of the Annual Conference of the International Speech Communication Assoc (INTERSPEECH 2016)

Editors

N Morgan

Pagination

2661-2665

ISBN

978-1-5108-3313-5

Department/School

School of Engineering

Publisher

International Speech and Communication Association

Place of publication

United States

Event title

17th Annual Conference of the International Speech Communication Association (INTERSPEECH 2016)

Event Venue

San Francisco

Date of Event (Start Date)

2016-09-08

Date of Event (End Date)

2016-09-16

Rights statement

Copyright 2016 ISCA

Repository Status

  • Restricted

Socio-economic Objectives

Clinical health not elsewhere classified

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