Instantaneous A Priori SNR Estimation by Cepstral Excitation Manipulation

As the <italic>a priori</italic> signal-to-noise ratio (SNR) contains crucial information about a signal's mixture of speech and noise, its estimation is subject to steady research. In this paper, we introduce a novel <italic> a priori</italic> SNR estimator based on synthesizing an idealized excitation signal in the cepstral domain. Our approach utilizes a source-filter decomposition in combination with a cepstral excitation manipulation in order to recreate an idealized excitation, which is subsequently shaped by an immanent envelope. In contrast to the well-known decision-directed approach by Ephraim and Malah, an <italic>instantaneous</italic> estimate is obtained, which is less prone to sudden acoustic environmental changes and musical noise. Additionally, the proposed estimator is able to preserve weak harmonic structures resulting in a spectrum that is more full-bodied. We present both a speaker-independent and a speaker-dependent variant of the new <italic>a priori</italic> SNR estimator, both showing more than 2 dB <inline-formula><tex-math notation="LaTeX">$\Delta \textrm {SNR}$</tex-math></inline-formula>  improvement versus state of the art, without any significant increase in speech distortion.