Expressive Quantization of Complex Rhythmic Structures for Automatic Music Transcription
نویسنده
چکیده
Two quantization models for ‘expressive’ rendering of complex rhythmic patterns are discussed. A multinesting quantizer captures expressivity by allowing fine-grained/high-quality resolution, thus covering the automatic transcription of a wide range of rhythmic configurations, yielding from simple to rather complex music notations. A look-up table quantizer is discussed as another model to attain expressivity and musical consistency; input is quantized by comparison of 'rhythmic similarity' from a user-defined data-set or look-up 'dictionary'. Both quantizers are presented as computing assisting tools to facilitate the transcription of rhythmic structures into the symbolic domain (i.e. music notation).
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