9th Annual Conference of the International Speech Communication Association

Brisbane, Australia
September 22-26, 2008

Robust Voiced/Unvoiced Speech Classification Using Empirical Mode Decomposition and Periodic Correlation Model

Md. Khademul Islam Molla, Keikichi Hirose, Nobuaki Minematsu

University of Tokyo, Japan

This paper presents a method of voiced/unvoiced (V/Uv) classification of noisy speech signals. Empirical mode decomposition (EMD), a newly developed tool to analyze nonlinear and non-stationary signals is used to filter the additive noise with the speech signal. The normalized autocorrelation of the filtered speech signal is computed to enhance the periodicity if any. It is considered that the voiced speech signal is periodically correlated and the unvoiced signal is not. A statistical model of determining periodic correlation is used to differentiate voiced and unvoiced speech with low SNR. The experimental results show that the use of EMD improves the classification performance and the overall efficiency is noticeable as compared to other existing algorithms.

Full Paper

Bibliographic reference.  Molla, Md. Khademul Islam / Hirose, Keikichi / Minematsu, Nobuaki (2008): "Robust voiced/unvoiced speech classification using empirical mode decomposition and periodic correlation model", In INTERSPEECH-2008, 2530-2533.