Speech Enhancement by Reconstruction from Cleaned Acoustic Features

This paper proposes a novel method of speech enhancement that moves away from conventional filtering-based methods and instead aims to reconstruct clean speech from a set of speech features. Underlying the enhancement system is a speech model which at present is based on a sinusoidal model. This is driven by a set of speech features, comprising voicing, fundamental frequency and spectral envelope, that are extracted from the noisy speech. A maximum a posteriori approach is proposed for estimating clean spectral envelope features from the noisy spectral envelope. A set of subjective tests, measuring speech quality, noise intrusiveness and overall quality, found the proposed method to be highly effective at removing noise. Comparison against conventional speech enhancement methods found performance to be equivalent to Wiener filtering.