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Article Dans Une Revue Journal of the Acoustical Society of America Année : 2013

Automated segmentation of linear time-frequency representations of marine-mammal sounds

Résumé

Many marine mammals produce highly nonlinear frequency modulations. Determining the time-frequency support of these sounds offers various applications, which include recognition, localization, and density estimation. This study introduces a low parameterized automated spectrogram segmentation method that is based on a theoretical probabilistic framework. In the first step, the background noise in the spectrogram is fitted with a Chi-squared distribution and thresholded using a Neyman-Pearson approach. In the second step, the number of false detections in time-frequency regions is modeled as a binomial distribution, and then through a Neyman-Pearson strategy, the time-frequency bins are gathered into regions of interest. The proposed method is validated on real data of large sequences of whistles from common dolphins, collected in the Bay of Biscay (France). The proposed method is also compared with two alternative approaches: the first is smoothing and thresholding of the spectrogram; the second is thresholding of the spectrogram followed by the use of morphological operators to gather the time-frequency bins and to remove false positives. This method is shown to increase the probability of detection for the same probability of false alarms
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Dates et versions

hal-00874945 , version 1 (19-10-2013)

Identifiants

Citer

Florian Dadouchi, Cedric Gervaise, Cornel Ioana, Julien Huillery, Jerome I. Mars. Automated segmentation of linear time-frequency representations of marine-mammal sounds. Journal of the Acoustical Society of America, 2013, 134 (3), pp.2546-2555. ⟨10.1121/1.4816579⟩. ⟨hal-00874945⟩
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