A matlab toolbox for musical feature extraction from audio. MIRtoolbox offers an integrated set of functions written in Matlab, dedicated to the extraction from audio files of musical features such as tonality, rhythm, structures, etc. The objective is to offer an overview of computational approaches in the area of Music Information Retrieval. The design is based on a modular framework: the different algorithms are decomposed into stages, formalized using a minimal set of elementary mechanisms. These building blocks form the basic vocabulary of the toolbox, which can then be freely articulated in new original ways. These elementary mechanisms integrates all the different variants proposed by alternative approaches - including new strategies we have developed -, that users can select and parametrize. This synthetic digest of feature extraction tools enables a capitalization of the originality offered by all the alternative strategies. Additionally to the basic computational processes, the toolbox also includes higher-level musical feature extraction tools, whose alternative strategies, and their multiple combinations, can be selected by the user.

References in zbMATH (referenced in 8 articles )

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  1. Meinard Müller; Frank Zalkow: libfmp: A Python Package for Fundamentals of Music Processing (2021) not zbMATH
  2. Chapaneri, Santosh; Jayaswal, Deepak: Structured Gaussian process regression of music mood (2020)
  3. Raphael Lenain, Jack Weston, Abhishek Shivkumar, Emil Fristed: Surfboard: Audio Feature Extraction for Modern Machine Learning (2020) arXiv
  4. İzmirli, Özgür: Constructing geometrical spaces from acoustical representations (2015)
  5. Arcos, Josep Lluis; Guaus, Enric; Ozaslan, Tan H.: Analyzing musical expressivity with a soft computing approach (2013) ioport
  6. Qu, Wen; Song, Kai-Song; Zhang, Yi-Fei; Feng, Shi; Wang, Da-Ling; Yu, Ge: A novel approach based on multi-view content analysis and semi-supervised enrichment for movie recommendation (2013) ioport
  7. Vatolkin, Igor; Preuß, Mike; Rudolph, Günter; Eichhoff, Markus; Weihs, Claus: Multi-objective evolutionary feature selection for instrument recognition in polyphonic audio mixtures (2012) ioport
  8. Rodà, Antonio: Perceptual tests and feature extraction: toward a novel methodology for the assessment of the digitization of old ethnic music records (2010)