DocumentCode :
1067989
Title :
Quality improvement of LPC-processed noisy speech by using spectral subtraction
Author :
Kang, G.S. ; Fransen, L.J.
Author_Institution :
US Naval Res. Lab., Washington, DC, USA
Volume :
37
Issue :
6
fYear :
1989
fDate :
6/1/1989 12:00:00 AM
Firstpage :
939
Lastpage :
942
Abstract :
Numerous noise-suppression techniques have been developed for operating at the front end of low-bit-rate digital voice terminals. Some of these techniques have been evaluated by standardized intelligibility tests such as the diagnostic rhyme test (DRT). It is well known that the use of a noise suppressor seldom improves the DRT score even though listeners have had the impression that speech quality was enhanced. Unfortunately, noise suppressors have only occasionally been evaluated by standardized quality tests. The authors supplement quality test data for reference purposes. They use the diagnostic acceptability measure (DAM) to evaluate speech quality of the latest 2400-b/s linear-predictive coder (LPC) with a noise suppressor at the front end. They used a spectral subtraction technique for noise suppression. Ten different sets of noisy speech recorded at actual military platforms (such as a helicopter, tank, turboprop, helicopter carrier, or jeep) were input sources. The magnitude of the DAM improvement is substantial: as much as six points on the average, which is large enough to upgrade speech quality somewhat
Keywords :
encoding; filtering and prediction theory; interference suppression; speech analysis and processing; speech intelligibility; voice communication; 2400 bit/s; LPC-processed noisy speech; diagnostic acceptability measure; front-end noise suppressor; intelligibility tests; linear-predictive coder; low-bit-rate digital voice terminals; military platforms; noise-suppression techniques; spectral subtraction; speech quality evaluation; Acoustics; Digital signal processing; Helicopters; Linear predictive coding; Noise measurement; Signal processing algorithms; Speech analysis; Speech enhancement; Subtraction techniques; Testing;
fLanguage :
English
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
0096-3518
Type :
jour
DOI :
10.1109/ASSP.1989.28065
Filename :
28065
Link To Document :
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