Type of Document	Dissertation
Author	Berg, Brian LaRoy
URN	etd-08172001-164442
Title	Investigating Speaker Features From Very Short Speech Records
Degree	PhD
Department	Electrical and Computer Engineering
Advisory Committee	Advisor Name Title A. A. (Louis) Beex Committee Chair Hugh F. VanLandingham Committee Member Ira Jacobs Committee Member Jeffrey H. Reed Committee Member Joe Ball Committee Member
Keywords	Digital Signal Processing Speech Analysis Speech Synthesis Speaker Recognition Speaker Identity Verification Speech Processing
Date of Defense	2001-07-23
Availability	unrestricted
Abstract A procedure is presented that is capable of extracting various speaker features, and is of particular value for analyzing records containing single words and shorter segments of speech. By taking advantage of the fast convergence properties of adaptive filtering, the approach is capable of modeling the nonstationarities due to both the vocal tract and vocal cord dynamics. Specifically, the procedure extracts the vocal tract estimate from within the closed glottis interval and uses it to obtain a time-domain glottal signal. This procedure is quite simple, requires minimal manual intervention (in cases of inadequate pitch detection), and is particularly unique because it derives both the vocal tract and glottal signal estimates directly from the time-varying filter coefficients rather than from the prediction error signal. Using this procedure, several glottal signals are derived from human and synthesized speech and are analyzed to demonstrate the glottal waveform modeling performance and kind of glottal characteristics obtained therewith. Finally, the procedure is evaluated using automatic speaker identity verification.
Files	Filename       Size       Approximate Download Time (Hours:Minutes:Seconds)     28.8 Modem   56K Modem   ISDN (64 Kb)   ISDN (128 Kb)   Higher-speed Access    afrif_berg.pdf 10.31 Mb 00:47:45 00:24:33 00:21:29 00:10:44 00:00:55

If you have questions or technical problems, please Contact DLA.