MUSCLE eTeam: Semantic from Audio

(MUSCLE NoE | All e-teams)


We will investigate and develop special methods for extracting features sets in audio and musical signals. We will also try to make a sort of "quasi"-object detection in audio signals. These extracted features will be used for several applications as music/instruments classification and retrieval (TU Wien, AUTH, ISTI-CNR), dynamic optimization of a digital signal processing algorithm for an enhancement of recorded music (ISTI-CNR, CUED Cambridge), etc. We will also work on the extension of a C++ library for audio processing and synthesis, which could be used for optimizing the feature extraction processes and, more in general, for audio/musical applications (ISTI-CNR, UNIS).

The results will be: The result of this e-team in the first stage would thus provide a kind of practical state-of-the-art showcase of the capabilities and competences on feature extraction and semantic annotation within MUSCLE.


Contribution of partners


The focus of this e-Team is particularly on encouraging collaboration between participants via exchange of tools as well as know-how concerning
their specific audio analysis tools. The goal here is to evaluate the suitability of the respective tools for the variety of heterogeneous tasks addressed in the various labs. This will be achieved by a set of short-term exchange visits in order to jointly work on processing the respective audio
data and study the results of the impact of the different approaches.

Tentative plan of activities

Further Infos


Graziano Bertini  
Istituto di Scienza e Tecnologie dell'Informazione, Consiglio Nazionale delle Ricerche
ISTI-CNR, Area di Ricerca CNR, Via G. Moruzzi, 1
56124 Pisa, Italy
Tel: +39 050 3153125  - +39 050 3153144 (lab.)
Mobile: +39 348 3972163
Fax: +39 050 3152810
e-mail: graziano.bertiniATisti.cnr.it

Andreas Rauber
Dept. of Software Technology and Interactive Systems
Vienna Univ. of Technology
Favoritenstr. 9 - 11 / 188
A - 1040 Wien
AUSTRIA e-mail: rauber@ifs.tuwien.ac.at