DocumentCode
2811280
Title
Music dereverberation using harmonic structure source model and Wiener filter
Author
Yasuraoka, Naoki ; Yoshioka, Takuya ; Nakatani, Tomohiro ; Nakamura, Atsushi ; Okuno, Hiroshi G.
Author_Institution
Grad. Sch. of Inf., Kyoto Univ., Kyoto, Japan
fYear
2010
fDate
14-19 March 2010
Firstpage
53
Lastpage
56
Abstract
This paper proposes a dereverberation method for musical audio signals. Existing dereverberation methods are designed for speech signals and are not necessarily effective for suppressing long and dense reverberation in musical audio signals because: 1) an all-pole model and a non-parametric model, which are used to represent source spectra, do not match musical tones, and 2) the conventional inverse-filter-based dereverberation is not effective for suppressing long and dense reverberation. To overcome the two problems, an appropriate dereverberation approach for musical audio signals is established. The first problem is resolved by using a harmonic Gaussian mixture model (GMM) to accurately model the harmonic structure of a source spectrum. The second problem is resolved by performing dereverberation with a Wiener filter based on both an estimated inverse filter and an estimated source spectrum model. Experimental results reveal the effectiveness of the proposed dereverberation method using these two solutions.
Keywords
Gaussian distribution; Wiener filters; acoustic signal processing; audio signal processing; music; reverberation; Wiener filter; all-pole model; conventional inverse-filter-based dereverberation; harmonic Gaussian mixture model; harmonic structure source model; music dereverberation; musical audio signals; musical tones; nonparametric model; source spectrum; Audio recording; Filtering; Informatics; Multiple signal classification; Power harmonic filters; Reverberation; Signal processing; Signal resolution; Speech processing; Wiener filter; Wiener filter; dereverberation; harmonic GMM; music signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location
Dallas, TX
ISSN
1520-6149
Print_ISBN
978-1-4244-4295-9
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2010.5496223
Filename
5496223
Link To Document