@article{(Open Science Index):https://publications.waset.org/pdf/16525,
	  title     = {A New Time-Frequency Speech Analysis Approach Based On Adaptive Fourier Decomposition},
	  author    = {Liming Zhang},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper, a new adaptive Fourier decomposition
(AFD) based time-frequency speech analysis approach is proposed.
Given the fact that the fundamental frequency of speech signals often
undergo fluctuation, the classical short-time Fourier transform (STFT)
based spectrogram analysis suffers from the difficulty of window size
selection. AFD is a newly developed signal decomposition theory. It is
designed to deal with time-varying non-stationary signals. Its
outstanding characteristic is to provide instantaneous frequency for
each decomposed component, so the time-frequency analysis becomes
easier. Experiments are conducted based on the sample sentence in
TIMIT Acoustic-Phonetic Continuous Speech Corpus. The results
show that the AFD based time-frequency distribution outperforms the
STFT based one.
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {7},
	  number    = {7},
	  year      = {2013},
	  pages     = {938 - 942},
	  ee        = {https://publications.waset.org/pdf/16525},
	  url   	= {https://publications.waset.org/vol/79},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 79, 2013},