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Reconnaissance d'accords à partir de signaux audio par l'utilisation de gabarits théoriques

Abstract : This thesis is in line with the music signal processing field and focuses in particular on the automatic chord transcription from audio signals. Indeed, for the past ten years, numerous works have aimed at representing music signals in a compact and relevant way, for example for indexation or music similarity search. Chord transcription constitutes a simple and robust way of extracting harmonic and rhythmic information from songs and can notably be used by musicians to playback musical pieces. We propose here two approaches for automatic chord recognition from audio signals, which are based only on theoretical chord templates, that is to say on the chord definitions. In particular, our systems neither need extensive music knowledge nor training. Our first approach is deterministic and relies on the joint use of chord templates, measures of fit and post-processing filtering. We first extract from the signal a succession of chroma vectors, which are then compared to chord templates thanks to several measures of fit. The so defined recognition criterion is then filtered, so as to take into account the temporal aspect of the task. The detected chord for each frame is finally the one minimizing the recognition criterion. This method notably entered an international evaluation (MIREX 2009) and obtained very fair results. Our second approach is probabilistic and builds on some components introduced in our deterministic method. By drawing a parallel between measures of fit and probability models, we can define a novel probabilistic framework for chord recognition. The probability of each chord in a song is learned from the song through an Expectation-Maximization (EM) algorithm. As a result, a relevant and sparse chord vocabulary is extracted for every song, which in turn leads to better chord transcriptions. This method is compared to numerous state-of-the-art systems, with several corpora and metrics, which allow a complete and multi-facet evaluation.
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Submitted on : Friday, December 3, 2010 - 4:37:49 PM
Last modification on : Saturday, January 9, 2021 - 5:40:49 PM
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  • HAL Id : pastel-00542840, version 1



Laurent Oudre. Reconnaissance d'accords à partir de signaux audio par l'utilisation de gabarits théoriques. Traitement du signal et de l'image [eess.SP]. Télécom ParisTech, 2010. Français. ⟨pastel-00542840⟩



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