ISBN 9783843947459

978-3-8439-4745-9, Reihe Elektrotechnik

Dörte Fischer
Single-Microphone Multi-Frame Speech Enhancement Exploiting Speech Interframe Correlation

150 Seiten, Dissertation Carl von Ossietzky Universität Oldenburg (2020), Hardcover, B5

Zusammenfassung / Abstract

Speech communication devices such as hearing aids or mobile phones are often used in acoustically challenging situations, where the desired speech signal is affected by undesired background noise. Since, in these situations speech quality and speech intelligibility may be degraded, speech enhancement algorithms are required to suppress the undesired background noise, while preserving the desired speech signal. In this thesis, we focus on single-microphone speech enhancement algorithms in the short-time Fourier transform domain, more in particular on multi-frame algorithms that aim at exploiting speech correlation across time-frames. In principle, exploiting the speech interframe correlation enables to suppress the undesired background noise, while keeping speech distortion low. Existing single-microphone multi-frame speech enhancement algorithms, such as the multi-frame minimum variance distortionless response (MFMVDR) filter and the multi-frame minimum power distortionless response (MFMPDR) filter, depend on the normalized speech correlation vector, which is highly time-varying and hence difficult to be accurately estimated.

The main objective of this thesis is to develop and evaluate novel robust methods to estimate the normalized speech correlation vector from the noisy microphone signal, either based on robust beamforming approaches or exploiting a low-rank speech model.