CUED Publications database

Bayesian classification of acoustical waveforms under environmental variability

Christensen, JEN and Godsill, SJ (2011) Bayesian classification of acoustical waveforms under environmental variability. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. pp. 281-284.

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We present in this paper a new multivariate probabilistic approach to Acoustic Pulse Recognition (APR) for tangible interface applications. This model uses Principle Component Analysis (PCA) in a probabilistic framework to classify tapping pulses with a high degree of variability. It was found that this model, achieves a higher robustness to pulse variability than simpler template matching methods, specifically when allowed to train on data containing high variability. © 2011 IEEE.

Item Type: Article
Uncontrolled Keywords: Acoustic pulse recognition Bayesian classification PCA tangible interface
Divisions: Div F > Signal Processing and Communications
Depositing User: Cron job
Date Deposited: 16 Jul 2015 13:51
Last Modified: 27 Nov 2015 11:05
DOI: 10.1109/ASPAA.2011.6082283