| ORIGINAL ARTICLE |
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| Year : 2015 | Volume
: 1
| Issue : 2 | Page : 119-123 |
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Forensic Automatic Speaker Recognition Based on Likelihood Ratio Using Acoustic-phonetic Features Measured Automatically
Huapeng Wang1, Cuiling Zhang2
1 Department of Forensic Science and Technology, National Police University of , Shenyang, Liaoning, China
2 School of Criminal Investigation, Southwest University of Political Science and Law, No. 301, Baosheng Ave, Yubei District, Chongqing, China
Correspondence Address:
Huapeng Wang
Department of Forensic Science and Technology, National Police University of China, Shenyang, Liaoning - 110 854
China
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/2349-5014.169617
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Forensic speaker recognition is experiencing a remarkable paradigm shift in terms of the evaluation framework and presentation of voice evidence. This paper proposes a new method of forensic automatic speaker recognition using the likelihood ratio framework to quantify the strength of voice evidence. The proposed method uses a reference database to calculate the within- and between-speaker variability. Some acoustic-phonetic features are extracted automatically using the software VoiceSauce. The effectiveness of the approach was tested using two Mandarin databases: A mobile telephone database and a landline database. The experiment's results indicate that these acoustic-phonetic features do have some discriminating potential and are worth trying in discrimination. The automatic acoustic-phonetic features have acceptable discriminative performance and can provide more reliable results in evidence analysis when fused with other kind of voice features. |
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