ARTIFICIAL-INTELLIGENCE AND MUSICAL COGNITION

被引:7
|
作者
LONGUETHIGGINS, HC
机构
[1] UNIV PENN, PHILADELPHIA, PA 19104 USA
[2] UNIV GLASGOW, GLASGOW, LANARK, SCOTLAND
[3] UNIV EDINBURGH, EDINBURGH, MIDLOTHIAN, SCOTLAND
[4] UCL, LONDON, ENGLAND
[5] UNIV WALES COLL CARDIFF, CARDIFF, S GLAM, WALES
[6] EPISTEMOL GRP, AYLESBURY, BUCKS, ENGLAND
[7] UNIV BIRMINGHAM, BIRMINGHAM, W MIDLANDS, ENGLAND
[8] UNIV SUSSEX, BRIGHTON BN1 9RH, E SUSSEX, ENGLAND
[9] TUFTS UNIV, MEDFORD, MA 02155 USA
关键词
D O I
10.1098/rsta.1994.0116
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
There has been much interest, in recent years, in the possibility of representing our musical faculties in computational terms. A necessary first step is to develop a formally precise theory of musical structure, and to this end, useful analogies may be drawn between music and natural language. Metrical rhythms resemble syntactic structures in being generated by phrase-structure grammars; as for the pitch relations between notes, the tonal intervals of Western music form a mathematical group generated by the octave, the fifth and the third. On this theoretical foundation one can construct AI programs for the transcription, editing and performance of classical keyboard music. A high degree of complexity and precision is required for the faithful representation of a sophisticated pianoforte composition, and to achieve a satisfactory level of performance it is essential to respect the minute variations of loudness and timing by which human performers reveal its hierarchical structure.
引用
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页码:103 / 113
页数:11
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