FEATURES EXTRACTION FOR MUSIC NOTES RECOGNITION USING HIDDEN MARKOV MODELS

Fco. Javier Salcedo, Jesús Díaz-Verdejo, José Carlos Segura

Abstract

In recent years Hidden Markov Models (HMMs) have been successfully applied to human speech recognition. The present article proves that this technique is also valid to detect musical characteristics, for example: musical notes. However, any recognition system needs to get a suitable set of parameters, that is, a reduced set of magnitudes that represent the outstanding aspects to classify an entity. This paper shows how a suitable parameterisation and adequate HMMs topology make a robust recognition system of musical notes. At the same time, the way to extract parameters can be used in other recognition technologies applied to music.

References

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Paper Citation


in Harvard Style

Javier Salcedo F., Díaz-Verdejo J. and Carlos Segura J. (2007). FEATURES EXTRACTION FOR MUSIC NOTES RECOGNITION USING HIDDEN MARKOV MODELS . In Proceedings of the Second International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2007) ISBN 978-989-8111-13-5, pages 180-187. DOI: 10.5220/0002139301800187


in Bibtex Style

@conference{sigmap07,
author={Fco. Javier Salcedo and Jesús Díaz-Verdejo and José Carlos Segura},
title={FEATURES EXTRACTION FOR MUSIC NOTES RECOGNITION USING HIDDEN MARKOV MODELS},
booktitle={Proceedings of the Second International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2007)},
year={2007},
pages={180-187},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002139301800187},
isbn={978-989-8111-13-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2007)
TI - FEATURES EXTRACTION FOR MUSIC NOTES RECOGNITION USING HIDDEN MARKOV MODELS
SN - 978-989-8111-13-5
AU - Javier Salcedo F.
AU - Díaz-Verdejo J.
AU - Carlos Segura J.
PY - 2007
SP - 180
EP - 187
DO - 10.5220/0002139301800187