DocumentCode
1707723
Title
AM-FM decomposition of speech signal using MWL criterion
Author
Far, Reza Rashidi ; Gazor, Saeed
Author_Institution
Dept. of Electr. & Comput. Eng., Queen´´s Univ., Kingston, Ont., Canada
Volume
3
fYear
2004
Firstpage
1769
Abstract
Adaptive maximum windowed likelihood algorithm is introduced and adapted to decompose the speech signal as an amplitude modulated-frequency modulated (AM-FM) signal. Choosing the window length and type, the algorithm can be adjusted to decompose different pieces of speech signal. By tuning the step size for each frequency, the algorithm can be tuned for each formant frequency. Simulations for two phonemes and an all voiced piece of speech show that the algorithm is able to track the formant frequencies successfully unless it is used in highly changing formants where some treatments have been suggested.
Keywords
adaptive filters; adaptive signal processing; amplitude modulation; frequency modulation; maximum likelihood estimation; speech processing; tuning; AM-FM speech signal decomposition; MWL criterion; adaptive filters; adaptive maximum windowed likelihood algorithm; algorithm tuning; all voiced speech piece; amplitude modulated-frequency modulated signal; formant frequency tracking; highly changing formants; phonemes; simulations; step size tuning; window length; window type; AWGN; Amplitude estimation; Amplitude modulation; Delay estimation; Frequency estimation; Signal processing; Signal processing algorithms; Signal synthesis; Speech processing; Speech synthesis;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Computer Engineering, 2004. Canadian Conference on
ISSN
0840-7789
Print_ISBN
0-7803-8253-6
Type
conf
DOI
10.1109/CCECE.2004.1349758
Filename
1349758
Link To Document