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Title: | Recognition of brand and models of cell-phones from recorded speech signals |
Authors: | Uludağ Üniversitesi/Mühendislik Fakültesi/Elektronik Mühendisliği Bölümü. Uludağ Üniversitesi/Mühendislik Fakültesi/Mekatronik Bölümü. Hanilci, Cemal Ertaş, Figen Ertaş, Tuncay Eskidere, Ömer AAH-4122-2021 AAH-4188-2021 S-4967-2016 35781455400 24724154500 6602486163 24723995200 |
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 |
Issue Date: | Apr-2012 |
Publisher: | Ieee-Inst Electrical Electronics Engineers |
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. |
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. |
URI: | https://doi.org/10.1109/TIFS.2011.2178403 https://ieeexplore.ieee.org/document/6096411 http://hdl.handle.net/11452/22885 |
ISSN: | 1556-6013 1556-6021 |
Appears in Collections: | Scopus Web of Science |
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