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Voice Separation A Local Optimization Approach Voice Separation A Local Optimization Approach Jurgen Kilian Holger H. Hoos Xiaodan Wu Feb. 26 2003.

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Presentation on theme: "Voice Separation A Local Optimization Approach Voice Separation A Local Optimization Approach Jurgen Kilian Holger H. Hoos Xiaodan Wu Feb. 26 2003."— Presentation transcript:

1 Voice Separation A Local Optimization Approach Voice Separation A Local Optimization Approach Jurgen Kilian Holger H. Hoos Xiaodan Wu Feb. 26 2003

2 Introduction  What is Voice Separation? (score) (score)  Some of the Usages  To obtain usable scores from performances of polyphonic music  To improve the music retrieval systems that only support monophonic music

3 Existing Approaches  Split Point Separation (figure) (figure)  Rule Based Approaches  Prefer small intervals between succeeding notes  Keep range of a voice small  Use a small number of voices  Avoid crossings of voices

4 Overview The method developed by the authors  Goal: To create reasonable and flexible score-notation for various needs  Technique and Algorithm  Preprocessing  The Cost Function  Stochastic Local Search Approach

5 Preprocessing  Removes small overlaps, quantizes the notes  Partitions the musical piece into slices.

6 The Cost Function  Pitch Distance Penalty Penalize large pitch intervals between successive notes in a voice.  Gap Distance Penalty Penalize large gaps/rests between successive notes in a voice.  Chord Distance Penalty Penalize chords with a large pitch interval between the highest and the lowest note in a voice, as well as irregular chords.  Overlap Distance Penalty Penalize overlaps between successive notes in the same voice.

7 Cost-Optimized Slice Separation  Using a stochastic local search approach  A fixed number of steps was employed to terminate the improvement

8 Implementation and Results  Implemented in midi2gmn, a program for converting MIDI into GUIDO Music Notation.  The code was written in ANSI C++.  All the penalty parameters and the maximum number of voices could be set in an initialization file.  With the correct parameter settings, the tested Bach chorals and inventions were separated almost entirely correctly.  Drawback: If a voice continues with a large interval step after a rest, the algorithm acts incorrectly.

9 Comments on the future work  Cost Functions could be improved by employing more rules in music theory.  The thought of Expectancy could be combined with the cost functions.

10 score

11 Split point separation


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