Abstract
In this paper we address the problem of enhancing single channel speech signal corrupted with additive background noise. We present a new scheme which utilizes a different time frequency representation along with the psychoacoustic features of human ear and combines these features with the well-known noise estimation method of minimum tracking. Instead of Fourier transform, we use a perceptual wavelet packet decomposition of speech, and perform spectral tracking and filtering on the envelope of the analytic signal.
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Omidi, M., Derakhshan, N., Hassan Savoji, M. (2008). The Advantage of Implementing Martin’s Noise Reduction Algorithm in Critical Bands Using Wavelet Packet Decomposition and Hilbert Transform. In: Sarbazi-Azad, H., Parhami, B., Miremadi, SG., Hessabi, S. (eds) Advances in Computer Science and Engineering. CSICC 2008. Communications in Computer and Information Science, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89985-3_100
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DOI: https://doi.org/10.1007/978-3-540-89985-3_100
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89984-6
Online ISBN: 978-3-540-89985-3
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