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
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;
Conference_Titel :
Electrical and Computer Engineering, 2004. Canadian Conference on
Print_ISBN :
0-7803-8253-6
DOI :
10.1109/CCECE.2004.1349758