Detection of Overlapping Acoustic Events using a Temporally-Constrained Probabilistic ModelReportar como inadecuado




Detection of Overlapping Acoustic Events using a Temporally-Constrained Probabilistic Model - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1 QMUL - Queen Mary University of London 2 IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes 3 Centre for Digital Music

Abstract : In this paper, a system for overlapping acoustic event detection is proposed, which models the temporal evolution of sound events. The system is based on probabilistic latent component analysis, supporting the use of a sound event dictionary where each exemplar consists of a succession of spectral templates. The temporal succession of the templates is controlled through event class-wise Hidden Markov Models HMMs. As input time-frequency representation, the Equivalent Rectangular Bandwidth ERB spectrogram is used. Experiments are carried out on polyphonic datasets of office sounds generated using an acoustic scene synthesizer-simulator, as well as real and synthesized monophonic datasets for comparative purposes. Results show that the proposed system outperforms several state-of-the-art methods for overlapping acoustic event detection on the same task, using both frame-based and event-based metrics, and is robust to varying event density and noise levels.

Keywords : Index Terms— Acoustic event detection probabilistic latent component analysis hidden Markov models





Autor: Emmanouil Benetos - Grégoire Lafay - Mathieu Lagrange - Mark Plumbley -

Fuente: https://hal.archives-ouvertes.fr/



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