Convolutive ICA-Based Forensic Speaker Identification Using Mel Frequency Cepstral Coefficients and Gaussian Mixture Models
| Autor: | José Apolinário Junior, Matheus Almeida Silveira, Rafael Timóteo de Sousa Júnior, Celso Oliveira, Cezar Schroeder, Joao Paulo C. L. da Costa, Antonio Manuel Rubio Serrano, Paulo Quintiliano |
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| Rok vydání: | 2013 |
| Předmět: | |
| Zdroj: | The International Journal of Forensic Computer Science. 8:27-34 |
| ISSN: | 1980-7333 1809-9807 |
| DOI: | 10.5769/j201301004 |
| Popis: | Automatic speaker identification techniques are widely used nowadays in forensic applications, but its accuracy harshly drops when the voice of the speaker of interest is immersed in a recording containing more than one voice, common situation of investigations where the targets voice are obtained through ambient recordings. In forensic applications where microphones are hidden, such interferent sound sources in recordings are common and they degrade severely the performance of speaker identification techniques. In this paper, we propose a method to mitigate this problem by spatially separating the voice of each speaker using a Blind Source Separation technique called Convolutive Independent Component Analysis, and then applying the separated speech signals to a speaker identification system based on Mel Frequency Cepstral Coefficients and Gaussian Mixture Models. For identifying more than one speaker, the proposed system has a better accuracy than the state-of-the-art solutions. |
| Databáze: | OpenAIRE |
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