NDLI: A time-varying analysis method for rapid transitions in speech

Content Provider	IEEE Xplore Digital Library
Author	Nathan, K.S. Lee, Y.-T. Silverman, H.F.
Copyright Year	1991
Abstract	A linear predictive coding (LPC) model based on time-dependent poles which has yielded promising results when applied to synthetic data is applied to real speech data. The data are processed pitch-synchronously using a simple procedure to identify regions of the data that best fit the model. The maximum-likelihood technique, which has been found to be robust in the presence of noise, is used to estimate the parameters. Resulting formant estimates for several diphthongs are presented. The algorithm tracks the formants well, both in stable regions and in regions of transition. This ability to track formant variation within analysis intervals is a definite advantage over traditional LPC. Results from speech data involving final stop consonants are presented. Rapid changes, particularly in the first and second formants, in the region immediately prior to the stop are detected. Such abrupt transitions are often not detected by traditional time-invariant methods.<>
Sponsorship	IEEE Signal Processing Society
Starting Page	815
Ending Page	824
Page Count	10
File Size	898425
File Format	PDF
ISSN	1053587X
Volume Number	39
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1991-04-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech analysis Parameter estimation Linear predictive coding Maximum likelihood estimation Data mining Difference equations Parameter extraction Maximum likelihood detection Noise robustness Parametric statistics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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