Automated speech analysis tools for children's speech production: A systematic literature review. (16th October 2018)

• Record Type: Journal Article
• Authors: McKechnie, J.; Ahmed, B.; Gutierrez-Osuna, R.; Monroe, P.; McCabe, P.; Ballard, K. J.
• Is Part Of: International journal of speech-language pathology. Volume 20:Number 6(2018)
• Page Start: 583
• Page End: 598
• Publication Date: 2018-10-16
• Subjects: automatic speech recognition -- speech sound disorder -- prosody; Speech disorders -- Periodicals; Language disorders -- Periodicals; Speech therapy -- Periodicals; 616.855005
• DOI: 10.1080/17549507.2018.1477991
• Languages: English
• ISSNs: 1754-9507

Abstract

Abstract: Purpose : A systematic search and review of published studies was conducted on the use of automated speech analysis (ASA) tools for analysing and modifying speech of typically-developing children learning a foreign language and children with speech sound disorders to determine (i) types, attributes, and purposes of ASA tools being used; (ii) accuracy against human judgment; and (iii) performance as therapeutic tools. Method : Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied. Across nine databases, 32 articles published between January 2007 and December 2016 met inclusion criteria: (i) focussed on children's speech; (ii) tools used for speech analysis or modification; and (iii) reporting quantitative data on accuracy. Result : Eighteen ASA tools were identified. These met the clinical threshold of 80% agreement with human judgment when used as predictors of intelligibility, impairment severity, or error category. Tool accuracy was typically <80% accuracy for words containing mispronunciations. ASA tools have been used effectively to improve to children's foreign language pronunciation. Conclusion : ASA tools show promise for automated analysis and modification of children's speech production within assessment and therapeutic applications. Further work is needed to train automated systems with larger samples of speech to increase accuracy for assessment and therapeutic feedback.