In a reverberant enclosure, acoustic speech signals are degraded by reflections from
walls, ceilings, and objects. Restoring speech quality and intelligibility from reverberated speech has received increasing interest over the past few years. Although multiple channel dereverberation methods provide some improvements in speech quality/
intelligibility, single-channel dereverberation remains an open challenge. Two types of advanced single-channel dereverberation methods, namely acoustic domain spectral subtraction and modulation domain filtering, provide small improvement in speech quality and intelligibility. In this thesis, we study single-channel dereverberation algorithms. Firstly, an
upper bound of time-frequency masking (TFM) performance for dereverberation is
obtained using ideal time-frequency masking (ITFM). ITFM has access to both the
clean and reverberated speech signals in estimating the binary-mask matrix. ITFM
implements binary masking in the short time Fourier transform (STFT) domain, preserving
only those spectral components less corrupted by reverberation. The experiment
results show that single-channel ITFM outperforms four existing multi-channel
dereverberation methods and suggest that large potential improvements could be
obtained using TFM for speech dereverberation. Secondly, a novel modulation domain spectral subtraction method is proposed for dereverberation. This method estimates modulation domain long reverberation spectral variance (LRSV) from time domain LRSV using a statistical room impulse response (RIR) model and implements spectral subtraction in the modulation domain. On one hand, different from acoustic domain spectral subtraction, our method
implements spectral subtraction in the modulation domain, which has been shown
to play an important role in speech perception. On the other hand, different from
modulation domain filtering which uses a time-invariant filter, our method takes the
changes of reverberated speech spectral variance along time into account and implements spectral subtraction adaptively. Objective and informal subjective tests show
that our proposed method outperforms two existing state-of-the-art single-channel
dereverberation algorithms. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2011-07-20 03:18:30.021
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OKQ.1974/6609 |
| Date | 25 July 2011 |
| Creators | ZHENG, CHENXI |
| Contributors | Queen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.)) |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner. |
| Relation | Canadian theses |
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