Title
A multiresolution ABS/OLA sinusoidal model using wavelet transform
Abstract
The sinusoidal model has been applied to a broad range of speech and audio coding, such as analysis/synthesis, time-and frequency-scale modification, fundamental frequency modification, speech enhancement, and co-channel separation. In this paper, we propose a multiresolution analysis-by-synthesis/overlap-add (ABS/OLA) sinusoidal model using a wavelet transform. In the proposed scheme, after decomposing an input speech signal into multiresolution subband signals using the wavelet transform, classical ABS/OLA sinusoidal models with different window lengths are applied to each subband signals respectively. It is shown that by applying a proper-sized analysis window, much more accurate sinusoidal components can be estimated. Experimental results have shown that the proposed multiresolution ABS/OLA sinusoidal model can achieve better performance than that of the classical ABS/OLA sinusoidal model in terms of the spectral characteristics, phase characteristics, and the quality of synthetic speech.
Year
DOI
Venue
2003
10.1109/ISSPA.2003.1224719
ISSPA (1)
Keywords
Field
DocType
speech signal decomposition,phase characteristic,audio coding,wavelet transforms,multiresolution sinusoidal model,fundamental frequency modification,synthetic speech quality,spectral analysis,transform coding,cochannel separation,speech analysis,speech synthesis,time-scale modification,spectral characteristic,frequency-scale modification,sinusoidal component estimation,speech coding,wavelet transform,signal resolution,window analysis,window length,overlap-add sinusoidal model,speech enhancement,multiresolution analysis-by-synthesis,wavelet analysis,fundamental frequency,multiresolution analysis
Speech enhancement,Speech synthesis,Fundamental frequency,Speech coding,Pattern recognition,Computer science,Transform coding,Artificial intelligence,Sinusoidal model,Wavelet transform,Wavelet
Conference
Volume
ISBN
Citations 
1
0-7803-7946-2
0
PageRank 
References 
Authors
0.34
1
2
Name
Order
Citations
PageRank
Ki-Hong Kim16114.23
In-Ho Hwang262.23