Machine Learning for Music
Our research on Machine Learning and Case-Based Reasoning systems has been applied to model different creative musical processes:
- The projects TABASCO and CBR-ProMusic have studied the issue of expressiveness in computer generated music.
- We are currently focused on the study of expressivity on professional violin performers
- We are exploring the design of a musical ecosystem for providing an enhanced musical creation environment.
- The PhD research of Claudio Baccigalupo is devoted on the desing of a Social Web Radio.
Visit our Machine Learning for Music web page.
- Case-Based Reasoning for Content-Based Music Processing01/12/2003 - 30/11/2006
The aim of the project is to work on different aspects of content-based music processing. The project will study and develop tools for musical content extraction, modeling, and processing. Specifically, we will investigate the use of artificial intelligence techniques, such as case-based reasoning, for content-based melody processing.
- Content-based Audio Transformation28/12/2000 - 27/12/2003
This project will study and develop a support tool for musical recording manipulation with the goal of enhancing sound and musical qualities in professional sound post production. Specifically, the project will address the description of musical attributes, music database storage and retrieval of those descriptions, and sound transformation based on descriptions using physical attributes (e.g. pitch), perceptual attributes (e.g. brightness), and musical knowledge (e.g. tension).
The components used for sound content analysis and description, as well as the components for physical manipulation of sound, are based on spectral modelling analysis and synthesis techniques. Moreover, the descriptions to be used will be compatible as far as possible with the future MPEG-7 standard for multimedia content description. The transformation components will use both case-based reasoning techniques and modelling of musical knowledge.
