An algorithm for formant frequency estimation from noise-corrupted speech signals

Authors

  • Shaikh Anowarul Fattah Centre for Signal Processing and Communications, Dept. of Electrical and Computer Engineering, Concordia University, Montreal, Que. H3G 1M8, Canada
  • Wei-Ping Zhu Centre for Signal Processing and Communications, Dept. of Electrical and Computer Engineering, Concordia University, Montreal, Que. H3G 1M8, Canada
  • M. Omair Ahmad Centre for Signal Processing and Communications, Dept. of Electrical and Computer Engineering, Concordia University, Montreal, Que. H3G 1M8, Canada

Keywords:

Acoustic signal processing, Algorithms, Error analysis, Least squares approximations, Frequency estimation algorithms, Natural sentences, Synthetic vowels

Abstract

An algorithm for format frequency estimation from noise-corrupted speech signals is presented. A scheme for frequency domain noise reduction and the ACF of the resulting noise-compensated speech signal is then employed in a modified form of least-squares Yule-Walker equations (LSYWE) to estimate poles of the VT system. A pole selection criterion is estimated for extracting the desired formats that enables the proposed scheme to avoid errors associated with weak formats. The proposed formant frequency estimation algorithm has been tested using different synthetic vowels synthesized using the Klatt synthesizer and natural vowels from the North Texas speech database as well as some natural sentences from the TIMIT speech database. Experimental results on natural and synthetic speech signals show the efficacy of the proposed method in estimating formant frequencies at a moderate to low levels of SNR.

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Published

2007-09-01

How to Cite

1.
Fattah SA, Zhu W-P, Ahmad MO. An algorithm for formant frequency estimation from noise-corrupted speech signals. Canadian Acoustics [Internet]. 2007 Sep. 1 [cited 2021 Dec. 7];35(3):110-1. Available from: https://jcaa.caa-aca.ca/index.php/jcaa/article/view/1925

Issue

Section

Proceedings of the Acoustics Week in Canada