Evaluation of a Speech Recognition Prototype for Speakers with Moderate and Severe Dysarthria: A Preliminary Report

Abstract

This study described preliminary work with the Supplemented Speech Recognition (SSR) system for speakers with dysarthria. SSR incorporated automatic speech recognition optimized for dysarthric speech, alphabet supplementation, and word prediction. Participants included seven individuals with a range of dysarthria severity. Keystroke savings using SSR averaged 68.2% for typical sentences and 67.5% for atypical phrases. This was significantly different to using word prediction alone. The SSR correctly identified an average of 80.7% of target stimulus words for typical sentences and 82.8% for atypical phrases. Statistical significance could not be claimed for the relations between sentence intelligibility and keystroke savings or sentence intelligibility and system performance. The results suggest that individuals with dysarthria using SSR could achieve comparable keystroke savings regardless of speech severity.

Keywords:

• Speech recognition
• Dysarthria
• Supplemented speech
• Voice recognition

Notes

1. Dragon NaturallySpeaking by Nuance, http://www.nuance.com/naturallyspeaking/

2. SpeakQ by Quillsoft Ltd., 2416 Queen Street East, Toronto, OntarioM1N 1A2, Canada, http://www.wordq.com

3. Vmax by Dynavox Mayer-Johnson, 2100 Wharton Street, Suite 400, Pittsburgh, PA 15203, [phone], http://www.dynavoxtech.com/products/v/

4. Toshiba Satellite R20, http://us.toshiba.com/computers/laptops/satellite

5. Andrea NC-7100 USB head mounted microphone by Andrea Electronics, http://www.andreaelectronics.com <http://www.andreaelectronics.com/>

Acknowledgements

This project was supported by the Eunice Kennedy Schriver National Institute of Child Health & Human Development under grant number 1R43HD047044-01. The authors thank the participants for their involvement in this project.

Declaration of interest: This work was completed on the first prototype of the Supplemented Speech Recognition System funded under the NIH SBIR grant 1R43HD047044-01. Tom Jakobs of Invotek, Inc. continues to develop this technology. The authors alone are responsible for the content and writing of this paper.