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%0 Conference Proceedings
%A Montecchio, Nicola
%A Cont, Arshia
%T A UNIFIED APPROACH TO REAL TIME AUDIO-TO-SCORE AND AUDIO-TO-AUDIO ALIGNMENT USING SEQUENTIAL MONTECARLO INFERENCE TECHNIQUES
%D 2011
%B International Conference on Acoustics and Speech Signal Processing (ICASSP)
%C Prague
%P 193-196
%F Montecchio11a
%K Score following
%K particle filtering
%K realtime
%X We present a methodology for the real time alignment of music signals using sequential Montecarlo inference techniques. The alignment problem is formulated as the state tracking of a dynamical system, and differs from traditional Hidden Markov Model - Dynamic Time Warping based systems in that the hidden state is continuous rather than discrete. The major contribution of this paper is addressing both problems of audio-to-score and audio-to-audio alignment within the same framework in a real time setting. Performances of the proposed methodology on both problems are then evaluated and discussed.
%1 6
%2 3
%U http://articles.ircam.fr/textes/Montecchio11a/