Exploring the Effectiveness of the Phase Features on Double Compressed AMR Speech Detection

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dc.authorid0000-0002-6404-1499
dc.contributor.authorBuker, Aykut
dc.contributor.authorHanilci, Cemal
dc.date.accessioned2026-02-08T15:15:54Z
dc.date.available2026-02-08T15:15:54Z
dc.date.issued2024
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractDetermining whether an audio signal is single compressed (SC) or double compressed (DC) is a crucial task in audio forensics, as it is closely linked to the integrity of the recording. In this paper, we propose the utilization of phase spectrum-based features for detecting DC narrowband and wideband adaptive multi-rate (AMR-NB and AMR-WB) speech. To the best of our knowledge, phase spectrum features have not been previously explored for DC audio detection. In addition to introducing phase spectrum features, we propose a novel parallel LSTM system that simultaneously learns the most representative features from both the magnitude and phase spectrum of the speech signal and integrates both sets of information to further enhance its performance. Analyses demonstrate significant differences between the phase spectra of SC and DC speech signals, suggesting their potential as representative features for DC AMR speech detection. The proposed phase spectrum features are found to perform as well as magnitude spectrum features for the AMR-NB codec, while outperforming the magnitude spectrum in detecting AMR-WB speech. The proposed phase spectrum features yield 8% performance improvement in terms of true positive rate over the magnitude spectrogram features. The proposed parallel LSTM system further improves DC AMR-WB speech detection.
dc.identifier.doi10.3390/app14114573
dc.identifier.issn2076-3417
dc.identifier.issue11
dc.identifier.scopus2-s2.0-85195991580
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.3390/app14114573
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6032
dc.identifier.volume14
dc.identifier.wosWOS:001246757400001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofApplied Sciences-Basel
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzWOS_KA_20260207
dc.subjectDC AMR speech detection
dc.subjectAMR-NB
dc.subjectAMR-WB
dc.subjectaudio forensics
dc.titleExploring the Effectiveness of the Phase Features on Double Compressed AMR Speech Detection
dc.typeArticle

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