Automatic Generation of Musical Instrument Detector by Using Evolutionary Learning Method
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- @InProceedings{Kobayashi:2009:ismir,
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author = "Yoshiyuki Kobayashi",
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title = "Automatic Generation of Musical Instrument Detector by
Using Evolutionary Learning Method",
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booktitle = "10th International Society for Music Information
Retrieval Conference",
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year = "2009",
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editor = "Keiji Hirata and George Tzanetakis",
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pages = "93--98",
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address = "Kobe, Japan",
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month = "26-30 " # oct,
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keywords = "genetic algorithms, genetic programming",
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URL = "http://ismir2009.ismir.net/proceedings/PS1-7.pdf",
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size = "6 pages",
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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