A METHOD OF SPEECH PERIODICITY ENHANCEMENT BASED ON TRANSFORM-DOMAIN SIGNAL DECOMPOSITION

Periodicity is an important property of speech signals. It plays a critical role in speech communication, especially when strong background noise is present. This paper presents a novel framework of periodicity enhancement for noisy speech. The enhancement operates on the linear prediction error (residual) signal. The residual signal goes through a constant-pitch time warping process and two sequential lapped frequency transforms, by which the periodic component is concentrated in the first modulation band. By emphasizing the respective transform coefficients, periodicity enhancement of noisy residual signal is achieved. The enhanced residual signal and estimated linear prediction filter parameters are used to synthesize the speech output. The effectiveness of the proposed method is confirmed consistently by various objective measures and subjective listening tests. It is observed that the enhanced speech can restore the harmonic structure of the original speech.