Title :
Time-correlation analysis of nonstationary signals with application to speech processing
Author :
Li, Ta-Hsin ; Gibson, Jerry D.
Author_Institution :
Texas A&M Univ., College Station, TX, USA
Abstract :
This paper proposes a new method of displaying and analyzing the evolutionary correlation structure of nonstationary signals. The method, called time-correlation analysis (TCA), is based on a filter-bank approach for stochastic signal characterization known as parametric filtering. Some properties of the TCA method are discussed that can be used to interpret the TCA plot. Examples of an application to speech analysis are given
Keywords :
correlation methods; filtering theory; speech processing; stochastic processes; time-domain analysis; TCA method; change detection; evolutionary correlation structure; filter-bank approach; nonstationary signals; parametric filtering; speech analysis; speech processing; stochastic signal characterization; time-correlation analysis; Autocorrelation; Filtering; Filters; Frequency; Signal analysis; Signal processing; Spectrogram; Speech analysis; Speech processing; White noise;
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1996., Proceedings of the IEEE-SP International Symposium on
Conference_Location :
Paris
Print_ISBN :
0-7803-3512-0
DOI :
10.1109/TFSA.1996.550089
