Non intrusive codec identification algorithm

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...

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Bibliographic Details
Main Authors: Sharma, D., Naylor, P. A., Gaubitch, N. D., Brookes, M.
Format: Conference Proceeding
Language:English
Subjects:
Automatic Diagnosis
Bit rate
Codecs
Encoding
GSM
Noise
Quality of Service
Speech
Speech CODEC Detection
Online Access:Request full text
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Description
Summary: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.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2012.6288914