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A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies

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JPCS_705_1_012037.pdf (1.306Mb)
Date
2016
Author
Ortiz P., D.
Villa, Luisa F.
Salazar, Carlos
Quintero, O.L.
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Abstract
A simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals -- The algorithm to define the dynamic threshold is a modification of a convex combination found in literature -- This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise -- The present work shows preliminary results over a database built with some political speech -- The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared -- Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works
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URI
http://dx.doi.org/10.1088/1742-6596/705/1/012037
http://hdl.handle.net/10784/8373
Editor URL
Journal of Physics: Conference Series; Vol. 705, Núm. 1 (2016); pp.9
DOI
10.1088/1742-6596/705/1/012037
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