Speech Dereverberation Using Nonnegative Convolutive Transfer Function and Spectro temporal Modeling

TL;DR

This paper introduces two novel single-channel speech dereverberation methods combining nonnegative convolutive transfer function and spectro-temporal modeling, significantly improving speech quality in reverberant environments.

Contribution

The paper proposes two new methods integrating NCTF and NMF models for speech dereverberation, including an extension exploiting temporal dependencies, with demonstrated superior performance.

Findings

Integrated method outperforms baseline NCTF and spectral enhancement methods.

Weighted method can outperform in quality measures depending on room acoustics.

Temporal dependency modeling benefits highly reverberant conditions.

Abstract

This paper presents two single channel speech dereverberation methods to enhance the quality of speech signals that have been recorded in an enclosed space. For both methods, the room acoustics are modeled using a nonnegative approximation of the convolutive transfer function (NCTF), and to additionally exploit the spectral properties of the speech signal, such as the low rank nature of the speech spectrogram, the speech spectrogram is modeled using nonnegative matrix factorization (NMF). Two methods are described to combine the NCTF and NMF models. In the first method, referred to as the integrated method, a cost function is constructed by directly integrating the speech NMF model into the NCTF model, while in the second method, referred to as the weighted method, the NCTF and NMF based cost functions are weighted and summed. Efficient update rules are derived to solve both optimization problems. In addition, an extension of the integrated method is presented, which exploits the temporal dependencies of the speech signal. Several experiments are performed on reverberant speech signals with and without background noise, where the integrated method yields a considerably higher speech quality than the baseline NCTF method and a state of the art spectral enhancement method. Moreover, the experimental results indicate that the weighted method can even lead to a better performance in terms of instrumental quality measures, but that the optimal weighting parameter depends on the room acoustics and the utilized NMF model. Modeling the temporal dependencies in the integrated method was found to be useful only for highly reverberant conditions.