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Agon C.

Ali Taylan Cemgil

Bert Kappen

Large E. W.

Peter Desain

Pressing J.

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Computer Music Journal

Rhythm Quantization for Transcription

Automatic Music Transcription is the extraction of an acceptable notation from performed music. One important task in this problem is rhythm quantization which refers to categorization of note durations. Although quantization of a pure mechanical performance is rather straightforward, the task becomes increasingly difficult in presence of musical expression, i.e. systematic variations in timing of notes and tempo changes. For quantization of natural performances, we employ a framework based on Bayesian statistics. We demonstrate that some simple quantization schemata can be derived in this framework by simple assumptions about timing deviations. A general quantization method, which can be derived in this framework, is vector quantization (VQ). The algorithm operates on short groups of onsets and is thus flexible in capturing the structure of timing deviations between neighboring onsets and thus performs better than simple rounding methods. Finally, we present some results on simple examples

Cemgil, A.T.

Desain, P.W.M.

Kappen, H.J.

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Contains fulltext :
                  112706.pdf (preprint version ) (Open Access)Proceedings of the AISB'99 Conventio

Radboud Repository

Rhythm quantization for transcription.

Item does not contain fulltextAutomatic Music Transcription is the extraction of an acceptable notation from performed music. One important task in this problem is rhythm quantization which refers to categorization of note durations. Although quantization of a pure mechanical performance is rather straightforward, the task becomes increasingly difficult in presence of musical expression, i.e. systematic variations in timing of notes and tempo changes. For quantization of natural performances, we employ a framework based on Bayesian statistics. We demonstrate that some simple quantization schemata can be derived in this framework by simple assumptions about timing deviations. A general quantization method, which can be derived in this framework, is vector quantization (VQ). The algorithm operates on short groups of onsets and is thus flexible in capturing the structure of timing deviations between neighboring onsets and thus performs better than simple rounding methods. Finally, we present some results on simple examples

Rhythm quantization for transcription

Rhythm quantization for transcription

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Radboud Repository

Radboud Repository

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Radboud Repository