Skip to Main content Skip to Navigation
Conference papers

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.
Complete list of metadata

Cited literature [8 references]  Display  Hide  Download

https://hal.inria.fr/hal-00692579
Contributor : Arshia Cont Connect in order to contact the contributor
Submitted on : Monday, April 30, 2012 - 11:42:53 PM
Last modification on : Tuesday, March 15, 2022 - 3:19:46 AM
Long-term archiving on: : Monday, November 26, 2012 - 4:00:44 PM

File

paper.pdf
Files produced by the author(s)

Identifiers

Citation

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. pp.193-196, ⟨10.1109/ICASSP.2011.5946373⟩. ⟨hal-00692579⟩

Share

Metrics

Record views

164

Files downloads

424