Audio as medium for content distribution (providing access to knowledge)

Reaching and educating the masses to the benefit of all of mankind is the ultimate goal and through the use of this technology facility/tool many can be reached in their own language, in their own community, in their own time and at their own pace. Making this content available to those who will benefit from the information, is vital. These people who want to consume the content are not necessarily that interested in the qualification, they need the information. Making the content available in an auditory format may also help those who may not be as literate as others. The uses of audio/ recorded lessons have a number of uses and should not just be seen as a medium for content distribution to distant communities. Recording lectures makes it possible for a lecturer to present lectures to a vast number of students, while just presenting the lecture once.

ACCEDA y BUSTREAMING : Integración de audio y video en el proceso de autoarchivo del Repositorio de la ULPGC en acceso abierto

Presentació de les dues noves plataformes desenvolupades per la Biblioteca de la Universitat de Las Palmas de Gran Canaria: ACCEDA (documentació científica de la ULPGC en accés obert) i BUSTREAMING (documentació multimèdia). Aquestes són dues noves iniciatives de la Biblioteca Universitària emmarcades dins del moviment Open Access, que se sumen a la ja existent Memòria Digital de Canàries, que es va iniciar l'any 2003 amb molt d'èxit. Tot i que el programari utilitzat per al desenvolupament d'ACCEDA és DSpace, la Biblioteca Universitària ha implementat serveis als usuaris i administradors, com per exemple, la possibilitat de dipositar documents sense haver d'utilitzar l'autoarxivament i la incorporació de l'eina BUStreaming desenvolupada per la pròpia Biblioteca.

A Musically aware system for browsing and interacting with audio music collections

In the context of the CompMusic project we are developing methods to automatically describe/annotate audio music recordings pertaining to various music cultures. As away to demonstrate the usefulness of the methods we are also developing a system to browse and interact with specific audio collections. The system is an online web application that interfaces with all the data gathered (audio, scores plus contextual information) and all the descriptions that are automatically generated with the developed methods. In this paper we present the basic architecture of the proposed system, the types of data sources that it includes,and we mention some of the culture specific issues that we are working on for its development. The system is in a preliminary stage but it shows the potential that MIR technologies can have in browsing and interacting with musiccollections of various cultures.

An approach for linking score and audio recordings in Makam music of Turkey

The main information sources to study a particular piece of music are symbolic scores and audio recordings. These are complementary representations of the piece and it isvery useful to have a proper linking between the two of the musically meaningful events. For the case of makam music of Turkey, linking the available scores with the correspondingaudio recordings requires taking the specificities of this music into account, such as the particular tunings, the extensive usage of non-notated expressive elements, and the way in which the performer repeats fragmentsof the score. Moreover, for most of the pieces of the classical repertoire, there is no score written by the original composer. In this paper, we propose a methodology to pair sections of a score to the corresponding fragments of audio recording performances. The pitch information obtained from both sources is used as the common representationto be paired. From an audio recording, fundamental frequency estimation and tuning analysis is done to compute a pitch contour. From the corresponding score, symbolic note names and durations are converted to a syntheticpitch contour. Then, a linking operation is performed between these pitch contours in order to find the best correspondences.The method is tested on a dataset of 11 compositions spanning 44 audio recordings, which are mostly monophonic. An F3-score of 82% and 89% are obtained with automatic and semi-automatic karar detection respectively,showing that the methodology may give us a needed tool for further computational tasks such as form analysis, audio-score alignment and makam recognition.