NDLI: A Pitch Detection Method for Speech Signals with Low Signal-to-Noise Ratio

Content Provider	IEEE Xplore Digital Library
Author	Shahnaz, C. Zhu, W.P. Ahmad, M.O.
Copyright Year	2007
Description	Author affiliation: Concordia Univ., Montreal (Shahnaz, C.; Zhu, W.P.; Ahmad, M.O.)
Abstract	A new method for the pitch detection of speech severely degraded by a white noise is presented in this paper. We intend to incorporate a noise reduction approach based on a modified power spectral subtraction scheme to enhance the pre-processed speech prior to pitch estimation. The de-noised speech is then passed through an inverse filter, whose parameters are derived from the linear prediction (LP) analysis, yielding an output referred to as the LP residual. Since the LP residual is capable of delivering the knowledge of glottal closure events, it is utilized to propose a new average magnitude sum function (AMSF) and an average magnitude difference function (AMDF) both of which exhibit the periodicity at the pitch period. Exploiting the property that the AMDF shows a notch while the AMSF produces a peak, the AMDF is weighted by the reciprocal of the AMSF to reinforce the pitch-harmonic-notches in a heavy noise. Simulation results using the Keele database guarantee a superior pitch detection efficacy of the proposed approach for a white noise-corrupted speech compared to some of the existing methods at a very low signal-to-noise ratio (SNR).
Starting Page	399
Ending Page	402
File Size	428421
Page Count	4
File Format	PDF
ISBN	1424414482
DOI	10.1109/ISSSE.2007.4294497
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-30
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal to noise ratio Speech enhancement Speech analysis Noise reduction White noise Speech coding Personal digital assistants Frequency Autocorrelation Background noise noise reduction pitch detection linear prediction
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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