DocumentCode
1257657
Title
An objective technique for evaluating doubletalk detectors in acoustic echo cancelers
Author
Cho, Jun H. ; Morgan, Dennis R. ; Benesty, Jacob
Author_Institution
Aware Inc., Bedford, MA, USA
Volume
7
Issue
6
fYear
1999
fDate
11/1/1999 12:00:00 AM
Firstpage
718
Lastpage
724
Abstract
Echo cancelers commonly employ a doubletalk detector (DTD), which is essential to keep the adaptive filter from diverging in the presence of near-end speech and other disruptive noise. There have been numerous algorithms to detect doubletalk in an acoustic echo canceler (AEC). In those applications, typically, the threshold is chosen only by some heuristic method and the performance evaluation is very subjective. In this study, we develop a way to objectively evaluate DTD algorithms based on the standard statistical methods of detection theory. A receiver operating characteristic (ROC) is derived to characterize DTD performance. Several DTD algorithms are examined and simulated under typical real-world operating conditions using measured room responses and signals taken from a digital speech database. The DTD methods are then evaluated and compared using the ROC metric
Keywords
acoustic correlation; acoustic receivers; acoustic signal detection; adaptive filters; adaptive signal detection; adaptive signal processing; architectural acoustics; correlation methods; echo suppression; filtering theory; statistical analysis; DTD algorithms; ROC metric; acoustic echo cancelers; adaptive filter; cross-correlation; detection theory; digital speech database; disruptive noise; doubletalk detectors; heuristic method; measured room responses; near-end speech; objective technique; performance evaluation; real-world operating conditions; receiver operating characteristic; simulation; standard statistical methods; threshold; Acoustic noise; Acoustic signal detection; Adaptive filters; Detectors; Finite impulse response filter; Jacobian matrices; Microphones; Noise cancellation; Speech enhancement; Statistics;
fLanguage
English
Journal_Title
Speech and Audio Processing, IEEE Transactions on
Publisher
ieee
ISSN
1063-6676
Type
jour
DOI
10.1109/89.799697
Filename
799697
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