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FP5

CUIDADO Résumé de rapport

Project ID: IST-1999-20194
Financé au titre de: FP5-IST
Pays: France

Online audio/music databases: Constraint solver and playlist generator

The CUIDADO project aimed at developing and experimenting innovative products and services relying on a comprehensive music/audio content-based approach.

This result address the problem of building automatically sequences of musical items, such as music titles or sound samples, taken from a large database. Indeed, building manually interesting playlists (sequences of music titles) out of large catalogues of songs, requires a expert musical knowledge of the database that most users do not have. Similarly, musical composition using sound samples requires an expert knowledge and musical sense of the sounds at your disposal.

We have implemented a general sequencing algorithm, which allows building these sequences automatically, in a computer-assisted way (see D2.5.3). This can handle both problems (items retrieval and sequence generation) at the same time: the user specifies the sequence properties and the system is able to build automatically the sequence out of musical items taken from very large databases. Indeed, the system we propose is able to scale up on databases containing more than 100.000 items, using a local search method based on constraint solving, called adaptive search.

The way the sequence is built is controlled by providing high-level properties, set by the user. The properties of the sequence are translated automatically into constraints holding on descriptors of the audio items. These constraints can be generic, such as “all items in the sequence should be different”, or can hold on properties of specific attributes of the items called “metadata”, such as “genre” or “duration” for music titles, and “pitch” or “percussivity” for sound samples. They can be local, holding on a specific item in the sequence, or can be global, holding on a part or even on the whole sequence. This formulation yields a hard combinatorial problem, as soon as the size of the database gets very large.

Thus filtering procedures have to be designed to find solutions in a reasonable time. We have implemented a constraint satisfaction method based on a local search technique, called adaptive search that is able to handle arbitrary complex constraints, and to scale up to large databases. It is an incomplete search algorithm that can yield approximate solutions very efficiently, and that is proven to be well adapted for musical applications.

The 2 specific applications of this general sequencing algorithm are:
- For sound samples: the musical mosaicing (“Musaicing”) of the Sound Palette.
- For music titles: the playlists generator of the Music Browser.

Contact

Francois PACHET, (Head of Music Unit)
Tél.: +33-1-44080505
Fax: +33-1-45878750
E-mail