JJAP Conf. Proc. 4, 011614 (2016) doi:10.7567/JJAPCP.4.011614
Adaptive speech recognition framework for dysarthric patients
- 1Doctoral School of Applied Informatics and Applied Mathematics, Óbuda University, Budapest, Hungary
- 2Institute of Mechatronics and Vehicle Engineering, Óbuda University, Budapest, Hungary
- 3Integrated Intelligent Systems Japanese-Hungarian Laboratory
- 4Department of Mathematics and Informatics, J. Selye University, Komarno, Slovakia
- Received September 27, 2015
- PDF (460 KB) |
Dysarthria is a speech disorder that mostly occurs as a symptom of neurodegenerative and other neuromuscular diseases. The speech of patients with dysarthria becomes distorted, the articulation of phonemes (especially that of consonants) is poor, the intelligibility and naturalness are impaired. Because dysarthria is progressive (similarly to the other symptoms of the main disease), patients may have difficulties using speech-controlled Ambient Assisted Living systems that could be a great help for them in daily life. In this paper, an adaptive speech recognition framework is introduced that is able to handle gradually occurring changes in the speech quality of the user. The presented technique can adapt to these changes while the speech interpretation accuracy of the system will not decrease, even in cases of noisy or incorrect training data.
Content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
- 1 L. Hartelius, B. Runmarker, and O. Andersen, Folia Phoniatrica et Logopaedica: Official Organ of the International Association of Logopedics and Phoniatrics (2000) p. 160.
- 2 B. Tomik and R. J. Guiloff, Amyotrophic Lateral Sclerosis 11, 4 (2010).
- 3 O. Kalinli et al., IEEE Trans. Audio Speech Lang. Process. 18, 1889 (2010).
- 4 C.-F. Juang and C.-T. Lin, IEEE Trans. Fuzzy Syst. 9, 139 (2001).
- 5 H. Wang, L. Wang, and X. Liu, Proc. 4th IEEE Int. Conf. on Information Science and Technology (ICIST), Shenzhen, 2014.
- 6 G. Riccardi and D. Hakkani-Tur, IEEE Trans. Speech Audio Process. 13, 504 (2005).
- 7 S. Xue et al., IEEE/ACM Trans. Audio Speech Lang. Process. 22, 1713 (2014).