Comparison of the wavelet and short time Fourier transforms for spectral analysis of speech signals

Authors:
Mohammad A. Tinati;Behzad Mozaffary
Affiliations:
Faculty of Electrical and Computer Engineering, Univercity of Tabriz, Tabriz, East Azerbaijan, Iran;Faculty of Electrical and Computer Engineering, Univercity of Tabriz, Tabriz, East Azerbaijan, Iran
Venue:
WAMUS'05 Proceedings of the 5th WSEAS International Conference on Wavelet Analysis and Multirate Systems
Year:
2005

Citing 4
Cited 0

Independent component analysis, a new concept?

Signal Processing - Special issue on higher order statistics
Time-frequency analysis: theory and applications

Time-frequency analysis: theory and applications
Blind source separation of acoustic mixtures using time-frequency domain independent component analysis

ICCS '02 Proceedings of the The 8th International Conference on Communication Systems - Volume 02
Blind separation of speech mixtures via time-frequency masking

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	0.01

Visualization

Abstract

In mixtures of speech signals the energy content of the components of the mixture is important and determine the structure of the mixture. Energy contents of signals are better shown when time-frequency or time-scale planes are used. In this paper we present a comparison of wavelet transform (WT) and short time Fourier Transform (STFT) in spectral analysis of speech signals. We will show in wavelet domain, speech signals are very uncorrelated and sparsity of signal is increased.