DocumentCode :
1653037
Title :
Speech dereverberation based on Linear Prediction: An Acoustic Vector Sensor approach
Author :
Shujau, Muawiyath ; Ritz, C.H. ; Burnett, Ian S.
Author_Institution :
Sch. of Electr., Comput., & Telecommun. Eng., Univ. of Wollongong, Wollongong, NSW, Australia
fYear :
2013
Firstpage :
639
Lastpage :
643
Abstract :
This paper introduces a dereverberation algorithm based on Linear Prediction (LP) applied to the outputs of an Acoustic Vector Sensor (AVS). The approach applies adaptive beamforming to take advantage of the directional outputs of the AVS array to obtain a more accurate LP spectrum than can be obtained with a single channel or Uniform Linear Array (ULA) with a comparable number of channels. This is then used within a modified version of the Spatiotemporal Averaging Method for Enhancement of Reverberant Speech (SMERSH) algorithm derived for the AVS to enhance the LP residual signal. In a highly reverberant environment, the approach demonstrates a significant improvement compared to a ULA as measured by both the Signal to Reverberant Ratio (SRR) and Speech to Reverberation Modulation Energy Ratio (SRMR) for sources ranging from at 1m to 5m from the array.
Keywords :
array signal processing; sensors; speech enhancement; vectors; AVS array; LP residual signal enhancement; SMERSH algorithm; SRMR; SRR; ULA; acoustic vector sensor approach; adaptive beamforming; linear prediction; signal to reverberant ratio; single channel; spatiotemporal averaging method for enhancement of reverberant speech algorithm; speech dereverberation; speech to reverberation modulation energy ratio; uniform linear array; Arrays; Microphones; Reverberation; Speech; Speech enhancement; Acoustic Vector Sensors; Dereverberation; Speech Enhancement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6637726
Filename :
6637726
Link To Document :
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