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
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;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4673-0045-2
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2012.6288914
