A Data Mining Approach to Expressive Music Performance Modeling
| Autor: | Amaury Hazan, Xavier Serra, Rafael Ramirez, Esteban Maestre |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Melody
MIDI business.industry Computer science Transcription (music) Speech recognition computer.file_format computer.software_genre Transformation (music) Set (abstract data type) Inductive logic programming Component (UML) Computer music Data mining Artificial intelligence business computer Natural language processing |
| Zdroj: | Multimedia Data Mining and Knowledge Discovery ISBN: 9781846284366 |
| Popis: | In this chapter we present a data mining approach to one of the most challenging aspects of computer music: modeling the knowledge applied by a musician when performing a score in order to produce an expressive performance of a piece. We apply data mining techniques to real performance data (i.e., audio recordings) in order to induce an expressive performance model. This leads to an expressive performance system consisting of three components: (1) a melodic transcription component that extracts a set of acoustic features from the audio recordings, (2) a data mining component that induces an expressive transformation model from the set of extracted acoustic features, and (3) a melody synthesis component that generates expressive monophonic output (MIDI or audio) from inexpressive melody descriptions using the induced expressive transformation model. We describe, explore, and compare different data mining techniques for inducing the expressive transformation model. |
| Databáze: | OpenAIRE |
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