Paper
14 December 2016 Development and testing of an audio forensic software for enhancing speech signals masked by loud music
Author Affiliations +
Proceedings Volume 10010, Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies VIII; 100103A (2016) https://doi.org/10.1117/12.2243356
Event: Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies 2016, 2016, Constanta, Romania
Abstract
In many situations audio recordings can decide the fate of a trial when accepted as evidence. But until they can be taken into account they must be authenticated at first, but also the quality of the targeted content (speech in most cases) must be good enough to remove any doubt. In this scope two main directions of multimedia forensics come into play: content authentication and noise reduction. This paper presents an application that is included in the latter. If someone would like to conceal their conversation, the easiest way to do it would be to turn loud the nearest audio system. In this situation, if a microphone was placed close by, the recorded signal would be apparently useless because the speech signal would be masked by the loud music signal. The paper proposes an adaptive filters based solution to remove the musical content from a previously described signal mixture in order to recover the masked vocal signal. Two adaptive filtering algorithms were tested in the proposed solution: the Normalised Least Mean Squares (NLMS) and Recursive Least Squares (RLS). Their performances in the described situation were evaluated using Simulink, compared and included in the paper.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert A. Dobre, Cristian Negrescu, and Dumitru Stanomir "Development and testing of an audio forensic software for enhancing speech signals masked by loud music", Proc. SPIE 10010, Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies VIII, 100103A (14 December 2016); https://doi.org/10.1117/12.2243356
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Digital filtering

Electronic filtering

Signal processing

Switches

Forensic science

Optical filters

Acoustics

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