Publication: Recognition of brand and models of cell-phones from recorded speech signals
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Authors
Hanilci, Cemal
Ertaş, Figen
Ertaş, Tuncay
Eskidere, Ömer
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Ieee-Inst Electrical Electronics Engineers
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Abstract
Speech signals convey various pieces of information such as the identity of its speaker, the language spoken, and the linguistic information about the text being spoken, etc. In this paper, we extract information about the cell phones from their speech records by using mel-frequency cepstrum coefficients and identify their brands and models. Closed-set identification rates of 92.56% and 96.42% have been obtained on a set of 14 different cell phones in the experiments using vector quantization and support vector machine classifiers, respectively.
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Keywords
Computer science, Engineering, Cell phone recognition, Mel-frequency cepstrum coefficients (MFCCs), Support vector machines (SVMs), Vector quantization (VQ), Support vector machines, Camera identification, Speaker recognition, Algorithm, Cellular telephones, Character recognition, Mobile phones, Speech recognition, Telecommunication equipment, Cell phone, Identification rates, Linguistic information, Mel frequency cepstrum coefficients, Speech signals, Support vector machine (SVM), Vector quantization
Citation
Hanilci, C. vd. (2012). "Recognition of brand and models of cell-phones from recorded speech signals". IEEE Transactions on Information Forensics and Security, 7(2), 625-634.