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Séminaire de Duong Hien Thanh, doctorant du Département Computer Vision de l'Institut MICA - Date : jeudi 8 décembre 2016, 14h00 - Lieu : salle séminaire, Institut MICA, Hanoi University of Science and Technology

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Intervenant :
DUONG Hien Thanh, doctorant du Département Computer Vision, Institut MICA

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Date : jeudi 8 décembre 2016, 14h00
Lieu : salle "seminar room", 9√®me √©tage, b√Ętiment B1, Institut MICA, Hanoi University of Science and Technology
Langue : le séminaire sera présenté en anglais

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We propose novel methods for automatically detecting non-stationary segments using non-negative matrix factorization (NMF) with aiming to effective sound annotation. For acoustic event detection or acoustic scene analysis, preparing a sufficient amount of training data is important. However, listening to all recorded signals and annotating them are very time-consuming. Assuming that the observed acoustic signal consists of a single stationary background sound and various short acoustic events, we apply NMF with single spectral basis for the spectrogram of the observed signal. Since it is expected that stationary background sound is well represented by NMF, the residual divergence is a good measure to detect non-stationary sound. Through experiments on nine real-world recordings of outside environmental sounds, we show that our methods effectively detect a variety of non-stationary sound segments.

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