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Statistical Based Audio Forensic on Identical Microphones

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 6 No. 5 (2016)

DOI
10.11591/ijece.v6i5.12022
ISSN
2088-8708, 2088-8708
Published
2016-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc-nd/4.0

Abstract

Microphone forensics has become a challenging field due to the proliferation of recording devices and explosion in video/audio recording. Video or audio recording helps a criminal investigator to analyze the scene and to collect evidences. In this regards, a robust method is required to assure the originality of some recordings. In this paper, we focus on digital audio forensics and study how to identify the microphone model. Defining microphone model will allow the investigators to conclude integrity of some recordings. We perform statistical analysis on the recording that is collected from two microphones of the same model. Experimental results and analysis indicate that the signal of sound recording of identical microphone is not exactly same and the difference is up to 1% - 3%.

Collaboration network of the authors

7 authors · 15 co-authorship links · 4 across different organisations

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  • University of Technology Malaysia
  • King Saud University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Ni'matus SholihahUniversity of Technology Malaysia2
Akmal RakhmadiUniversity of Technology Malaysia2
Dzulkifli MohamadUniversity of Technology Malaysia2

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Statistical Based Audio Forensic on Identical Microphones</dc:title><dc:creator>Kurniawan, Fajri</dc:creator><dc:creator>Mohd. Rahim, Mohd. Shafry</dc:creator><dc:creator>S. Khalil, Mohammed</dc:creator><dc:creator>Khurram Khan, Muhammad</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p&amp;gt;Microphone forensics has become a challenging field due to the proliferation of recording devices and explosion in video/audio recording. Video or audio recording helps a criminal investigator to analyze the scene and to collect evidences. In this regards, a robust method is required to assure the originality of some recordings. In this paper, we focus on digital audio forensics and study how to identify the microphone model. Defining microphone model will allow the investigators to conclude integrity of some recordings. We perform statistical analysis on the recording that is collected from two microphones of the same model. Experimental results and analysis indicate that the signal of sound recording of identical microphone is not exactly same and the difference is up to 1% - 3%.&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2016-10-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v6i5.12022</dc:identifier><dc:identifier>10.11591/ijece.v6i5.12022</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 6 No 5 (2016); 2211</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://www.iaescore.com/journals/index.php/IJECE/article/viewFile/1148/4205</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc-nd/4.0</dc:rights></oai_dc:dc>