PhDAs machines become more and more portable, and part of our everyday life, it becomes
apparent that developing interactive and ubiquitous systems is an important
aspect of new music applications created by the research community. We are interested
in developing a robust layer for the automatic annotation of audio signals, to
be used in various applications, from music search engines to interactive installations,
and in various contexts, from embedded devices to audio content servers. We
propose adaptations of existing signal processing techniques to a real time context.
Amongst these annotation techniques, we concentrate on low and mid-level tasks
such as onset detection, pitch tracking, tempo extraction and note modelling. We
present a framework to extract these annotations and evaluate the performances of
different algorithms.
The first task is to detect onsets and offsets in audio streams within short latencies.
The segmentation of audio streams into temporal objects enables various
manipulation and analysis of metrical structure. Evaluation of different algorithms
and their adaptation to real time are described. We then tackle the problem of
fundamental frequency estimation, again trying to reduce both the delay and the
computational cost. Different algorithms are implemented for real time and experimented
on monophonic recordings and complex signals. Spectral analysis can be
used to label the temporal segments; the estimation of higher level descriptions is
approached. Techniques for modelling of note objects and localisation of beats are
implemented and discussed.
Applications of our framework include live and interactive music installations,
and more generally tools for the composers and sound engineers. Speed optimisations
may bring a significant improvement to various automated tasks, such as
automatic classification and recommendation systems. We describe the design of
our software solution, for our research purposes and in view of its integration within
other systems.EU-FP6-IST-507142 project SIMAC (Semantic Interaction with Music
Audio Contents);
EPSRC grants GR/R54620; GR/S75802/01
