Abstract
This article focuses on the development of detection and classification system of environmental sounds in real-time in a typical home for persons with disabilities. Based on the extraction of acoustic characteristics (Mel Frequency Cepstral Coefficients, Zero Crossing Rate, Roll Off Point and Spectral Centroid) and using a probabilistic classifier (Gaussian Mixture Model), preliminary results show an accuracy rate greater than 93% in the detection and 98% in the classification task
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References
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© 2012 Springer-Verlag Berlin Heidelberg
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Lozano, H., Hernáez, I., Camarena, J., Díez, I., Navas, E. (2012). A Real-Time Sound Recognition System in an Assisted Environment. In: Miesenberger, K., Karshmer, A., Penaz, P., Zagler, W. (eds) Computers Helping People with Special Needs. ICCHP 2012. Lecture Notes in Computer Science, vol 7383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31534-3_57
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DOI: https://doi.org/10.1007/978-3-642-31534-3_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31533-6
Online ISBN: 978-3-642-31534-3
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