UID:
almahu_9947920629702882
Format:
XV, 210 p.
,
online resource.
ISBN:
9783540481270
Series Statement:
Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 746
Content:
This monograph presents the author's studies in music recognition aimed at developing a computer system for automatic notation of performed music. The performance of such a system is supposed to be similar to that of speech recognition systems: acoustical data at the input and music scoreprinting at the output. The approach to pattern recognition employed is thatof artificial perception, based on self-organizing input data in order to segregate patterns before their identification by artificial intelligencemethods. The special merit of the approach is that it finds optimal representations of data instead of directly recognizing patterns.
Note:
Correlativity of perception -- Substantiating the model -- Implementing the model -- Experiments on chord recognition -- Applications to rhythm recognition -- Applications to music theory -- General discussion -- Conclusions.
In:
Springer eBooks
Additional Edition:
Printed edition: ISBN 9783540573944
Language:
English
Subjects:
Computer Science
URL:
http://dx.doi.org/10.1007/BFb0019384
URL:
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