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Extraction d'information rythmique à partir d'enregistrements musicaux

Abstract : This dissertation presents work on the development of tools for the automated analysis of music signals, more exactly it proposes a number of techniques to identify and examine the fundamental elements of musical rhythm. There exist many applications requiring rhythmic information, for example automatic music transcription, music information retrieval, audio special effects, audio editing. The main research axis consisted in the development of techniques to estimate rhythmic parameters of music such as beat rates and beat localizations at two different metrical levels: the tatum and the tactus (or tempo). In this work, we have proposed to carry out the analysis after separating the audio signal in a deterministic part (containing the harmonic sounds) and the stochastic part (containing the residual signal after extracting the harmonic part from the original signal). We exploited the principle of the so-called Spectral Energy Flux, i.e., the rate of change of the power spectrum in audio signals as a function of time, to develop an effective algorithm to estimate the amount of musical stress at a given time. We have also presented a technique based on the dynamic programming algorithm which was specially conceived to track simultaneously the course of several rhythmic trajectories through time. The effectiveness of the whole system and of a number of its derivatives was validated using a database comprising 1435 musical pieces and covering ten musical genres. In addition, the developed algorithms were submitted to external evaluation within the framework of the international contest "Music Information Retrieval Evaluation eXchange (MIREX)" in the category of "tempo extraction", and in the edition of 2005 one of our algorithms obtained the first place among more than twelve submissions.
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Submitted on : Friday, May 4, 2007 - 8:00:00 AM
Last modification on : Saturday, January 9, 2021 - 5:34:41 PM
Long-term archiving on: : Thursday, September 30, 2010 - 7:56:27 PM


  • HAL Id : pastel-00002244, version 1



Miguel A. Alonso Arevalo. Extraction d'information rythmique à partir d'enregistrements musicaux. domain_other. Télécom ParisTech, 2006. English. ⟨pastel-00002244⟩



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