Automatic Generation of Musical Instrument Detector by Using Evolutionary Learning Method

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@InProceedings{Kobayashi:2009:ismir,

• author = "Yoshiyuki Kobayashi",
• title = "Automatic Generation of Musical Instrument Detector by Using Evolutionary Learning Method",
• booktitle = "10th International Society for Music Information Retrieval Conference",
• year = "2009",
• editor = "Keiji Hirata and George Tzanetakis",
• pages = "93--98",
• address = "Kobe, Japan",
• month = "26-30 " # oct,
• keywords = "genetic algorithms, genetic programming",
• URL = "http://ismir2009.ismir.net/proceedings/PS1-7.pdf",
• size = "6 pages",
• abstract = "This paper presents a novel way of generating information extractors that obtain high-level information from recorded music such as the presence of a certain musical instrument. Our information extractor is comprised of a feature set and a discrimination or regression formula. We introduce a scheme to generate the entire information extractor given only a large amount of labeled dataset. For example, data could be waveform, and label could be the presence of musical instruments in them. We propose a very flexible description of features that allows various kinds of data other than waveform. Our proposal also includes a modified evolutionary learning method to optimize the feature set. We applied our scheme to automatically generate musical instrument detectors for mixed-down music in stereo. The experiment showed that our scheme could find a suitable set of features for the objective and could generate good detectors.",

}

Genetic Programming entries for Yoshiyuki Kobayashi

Citations