A Unified Approach to Real Time Audio-to-Score and Audio-to-Audio Alignment Using Sequential Montecarlo Inference Techniques

Abstract : 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.
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ICASSP 2011 : Proceedings of International Conference on Acoustics, Speech and Signal Processing, May 2011, Prague, Czech Republic. IEEE, pp.193-196, 2011, 〈10.1109/ICASSP.2011.5946373〉
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Nicola Montecchio, Arshia Cont. A Unified Approach to Real Time Audio-to-Score and Audio-to-Audio Alignment Using Sequential Montecarlo Inference Techniques. ICASSP 2011 : Proceedings of International Conference on Acoustics, Speech and Signal Processing, May 2011, Prague, Czech Republic. IEEE, pp.193-196, 2011, 〈10.1109/ICASSP.2011.5946373〉. 〈hal-00692579〉

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