A long state vector Kalman filter for speech enhancement

File Size Format
51673_1.pdf 641Kb Adobe PDF View
Title A long state vector Kalman filter for speech enhancement
Author So, Stephen; Paliwal, Kuldip Kumar
Publication Title Proceedings of the 9th Annual Conference of the International Speech Communication Association
Editor Janet Fletcher, Deborah Loakes
Year Published 2008
Place of publication Lisbon, Portugal
Publisher International Speech Communication Association
Abstract In this paper, we investigate a long state vector Kalman filter for the enhancement of speech that has been corrupted by white and coloured noise. It has been reported in previous studies that a vector Kalman filter achieves better enhancement than the scalar Kalman filter and it is expected that by increasing the state vector length, one may improve the enhancement performance even further. However, any enhancement improvement that may result from an increase in state vector length is constrained by the typical use of short, non-overlapped speech frames, as the autocorrelation coefficient estimates tend to become less reliable at higher lags. We propose to overcome this problem by incorporating an analysis-modification-synthesis framework, where long, overlapped frames are used instead. Our enhancement experiments based on the NOIZEUS corpus show that the proposed long state vector Kalman filter achieves higher mean SNR and PESQ scores than the scalar and short state vector Kalman filter, therefore fulfilling the notion that a longer state vector can lead to better enhancement.
Peer Reviewed Yes
Published Yes
Publisher URI http://www.isca-speech.org/index.php
Alternative URI http://www.interspeech2008.org/
Copyright Statement Copyright 2008 ISCA and the Authors. The attached file is reproduced here in accordance with the copyright policy of the publisher. For information about this conference please refer to the conference’s website or contact the authors.
ISBN 1990-9772
Conference name Interspeech 2008 incorporating SST 2008
Location Australia
Date From 2008-09-22
Date To 2008-09-26
URI http://hdl.handle.net/10072/21299
Date Accessioned 2008-09-23
Language en_US
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Signal Processing
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

Show simple item record

Griffith University copyright notice