Title: Research Student
Research Group: Centre for Digital Music
Supervisor: Mark Sandler
Research Topic: Semantic Music Analysis for Intelligent Editing
Off-the-shelf sound editors for professional music production do not have formalized knowledge about the edited material, thus human-computer interaction is inefficient. We believe that recent development in music information retrieval, computational music understanding and audio analysis is capable of bringing about significant improvement. The primary motivation behind this research is the adaptation and development of music analysis tools for creative music production. The objective is to enhance the workflow and user experience in the post-production environment of contemporary popular music recordings in the broadest sense. The idea rises from the recognition that the fundamental way of editing music, even though it requires high level of human interaction with often cumbersome work, remains unchanged throughout the last decades. Our practical goal is enhancing sound editing routine through providing visual cues related to the music structure and intelligent context dependent functionality.
The research builds on technologies that have been developed in our centre for audio feature extraction and methods for inferring higher level meaning on these features in the perceptual, semantic or musical domain (e.g. note onset detection, perceptual or semantic segmentation). Which of these data proves to be the most relevant in developing an enhanced human interface is an open research question.
Our further aim is to provide more detailed and higher quality metadata using the Music Ontology, through having access to studio master recordings. This determines the focus of our current research into an extensible framework for describing audio features and studio processes.
G. Fazekas and M. B. Sandler. Intelligent Editing of Studio Recordings with the help of Automatic Music Structure Extraction. In Proceedings of the the 122nd Convention of the AES, May 5-8, 2007, Vienna, Austria.
G. Fazekas and M. B. Sandler. Structural decomposition of recorded vocal performances and its application to
intelligent audio editing. In Proceedings
of the the 123rd Convention of
the AES, October 5–8, 2007, New York, NY, USA.