Literature DB >> 20698428

Difficulties in automatic speech recognition of dysarthric speakers and implications for speech-based applications used by the elderly: a literature review.

Victoria Young1, Alex Mihailidis.   

Abstract

Despite their growing presence in home computer applications and various telephony services, commercial automatic speech recognition technologies are still not easily employed by everyone; especially individuals with speech disorders. In addition, relatively little research has been conducted on automatic speech recognition performance with older adults, in whom speech disorders are commonly present. As one ages, the older adult voice naturally begins to resemble some aspects of mildly dysarthric speech. Dysarthria, a common neuromotor speech disorder, is particularly useful for exploring performance limitations of automatic speech recognizers owing to its wide range of speech expression. This article reviews clinical research literature examining the use of commercial speech-to-text automatic speech recognition technology by individuals with dysarthria. The main factors limiting automatic speech recognition performance with dysarthric speakers are highlighted and extended to the elderly using a specific example of a novel, automated, speech-based personal emergency response system for older adults.

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Mesh:

Year:  2010        PMID: 20698428     DOI: 10.1080/10400435.2010.483646

Source DB:  PubMed          Journal:  Assist Technol        ISSN: 1040-0435


  8 in total

1.  Access interface strategies.

Authors:  Susan Fager; David R Beukelman; Melanie Fried-Oken; Tom Jakobs; John Baker
Journal:  Assist Technol       Date:  2011

2.  Using Virtual Technology to Promote Functional Communication in Aphasia: Preliminary Evidence From Interactive Dialogues With Human and Virtual Clinicians.

Authors:  Michelene Kalinyak-Fliszar; Nadine Martin; Emily Keshner; Alex Rudnicky; Justin Shi; Gregory Teodoro
Journal:  Am J Speech Lang Pathol       Date:  2015-11       Impact factor: 2.408

3.  Regularized Speaker Adaptation of KL-HMM for Dysarthric Speech Recognition.

Authors:  Myungjong Kim; Younggwan Kim; Joohong Yoo; Jun Wang; Hoirin Kim
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2017-03-13       Impact factor: 3.802

4.  A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders.

Authors:  Rohit Voleti; Julie M Liss; Visar Berisha
Journal:  IEEE J Sel Top Signal Process       Date:  2019-11-07       Impact factor: 6.856

5.  The Effects of Physically Embodied Multiple Conversation Robots on the Elderly.

Authors:  Toshiaki Nishio; Yuichiro Yoshikawa; Kazuki Sakai; Takamasa Iio; Mariko Chiba; Taichi Asami; Yoshinori Isoda; Hiroshi Ishiguro
Journal:  Front Robot AI       Date:  2021-03-22

6.  Acceptability of collecting speech samples from the elderly via the telephone.

Authors:  Catherine Diaz-Asper; Chelsea Chandler; R Scott Turner; Brigid Reynolds; Brita Elvevåg
Journal:  Digit Health       Date:  2021-04-17

7.  Logopenic and nonfluent variants of primary progressive aphasia are differentiated by acoustic measures of speech production.

Authors:  Kirrie J Ballard; Sharon Savage; Cristian E Leyton; Adam P Vogel; Michael Hornberger; John R Hodges
Journal:  PLoS One       Date:  2014-02-28       Impact factor: 3.240

8.  Automatic Assessment of Language Ability in Children with and without Typical Development.

Authors:  Robert Gale; Jill Dolata; Emily Prud'hommeaux; Jan van Santen; Meysam Asgari
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2020-07
  8 in total

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