Automated speech analysis tools for children’s speech production: A systematic literature review

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.

Keywords:

• automatic speech recognition
• speech sound disorder
• prosody

Acknowledgements

The statements made herein are solely the responsibility of the authors. Jacqueline McKechnie wishes to thank Yulia Ulyannikova from the University of Sydney Health Sciences Library for her time and expertise in database search syntax.

Declaration of interest

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was made possible by NPRP Grant # 8-293-2-124 (Ahmed, Osuna, Ballard) from the Qatar National Research Fund (a member of the Qatar Foundation) and an Australian Postgraduate Award (McKechnie). This work was supported by the Qatar National Research Fund (a member of the Qatar Foundation) [NPRP # 8-293-2-124].