Abstract
In this paper, we present experimental results on using vowels and one syllable words (VOSW) to activate some input device such as the control of mouse pointer on the screen. This type of Human Computer Interface might be used by a category of disabled person such as upper arm and finger stroke. Our goal is to design a system for the control of mouse cursor based on voice input command, using the pronunciation of certain vowels and some syllable words which can be produced even by persons affected by chronic inflammation of the larynx and vocal fold nodules. Linear predictive coefficients (LPC) and Mel Frequency Cepstral Coefficients (MFCCs) with derivatives are selected as features. Multiclass SVM then Hidden Markov Models (HMMs) have been tested as classifiers for matching components (vowels and short words). Tests and results using different features were are presented on tables, then the two classifiers were experimented independently and results were registered. Finally a verbal user interface has been designed and experienced on web page browser.
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Al-Dahoud, A., Fezari, M., Wassila, A., Al-Rawashdeh, T. (2016). Multiclass SVM/HMM Vowels Recognition System Towards Improving Human Computer Interaction. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds) Dependability Engineering and Complex Systems. DepCoS-RELCOMEX 2016. Advances in Intelligent Systems and Computing, vol 470. Springer, Cham. https://doi.org/10.1007/978-3-319-39639-2_1
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DOI: https://doi.org/10.1007/978-3-319-39639-2_1
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