DocumentCode
3163944
Title
Non intrusive codec identification algorithm
Author
Sharma, Dushyant ; Naylor, Patrick A. ; Gaubitch, Nikolay D. ; Brookes, Mike
Author_Institution
Centre for Law Enforcement Audio Res. (CLEAR), Imperial Coll. London, London, UK
fYear
2012
fDate
25-30 March 2012
Firstpage
4477
Lastpage
4480
Abstract
We present a non-intrusive data driven method for codec detection and identification in the presence of background noise. The method uses a number of speech features which are then used to train a CART classifier. We demonstrate the performance of the method using several different noise types over a wide range of SNRs. Our results show that we can identify a codec and its bit rate to an accuracy of 92% and we are able to detect the presence of a codec with an accuracy of 97% at -5 dB SNR.
Keywords
speech codecs; CART classifier; SNR; background noise; codec detection; nonintrusive codec identification algorithm; nonintrusive data driven method; speech features; Bit rate; Codecs; Databases; Encoding; GSM; Noise; Speech; Automatic Diagnosis; Quality of Service; Speech CODEC Detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location
Kyoto
ISSN
1520-6149
Print_ISBN
978-1-4673-0045-2
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2012.6288914
Filename
6288914
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