4th International Conference on Spoken Language Processing

Philadelphia, PA, USA
October 3-6, 1996

Nonlinear Estimation of DEGG Signals with Applications to Speech Pitch Detection

Kenneth E. Barner

Applied Science and Engineering Laboratories, University of Delaware/A.I. duPont Institute, Wilmington, DE, USA

Speech pitch detection remains a fundamental problem due to importance in numerous aspects of speech processing. Current pitch detectors focus on determining the Glottal Closure Instant (GCI). Accurate GCI measures can be obtained from the Differentiated Electroglottograph (DEGG) signal. Unfortunately, DEGG signals are not available in most practical applications. A novel method of pitch detection is proposed here based on the nonlinear estimation of DEGG signals from the acoustic speech waveform. This method requires the DEGG signals only during optimization. In operation, the proposed pitch detector marks glottal closures based strictly on the acoustical speech waveform. In addition to the algorithm development, performance comparison results are presented.

Full Paper

Bibliographic reference.  Barner, Kenneth E. (1996): "Nonlinear estimation of DEGG signals with applications to speech pitch detection", In ICSLP-1996, 2243-2246.