A compositional approach to analysis re-synthesis
This report summarises the work achieved in the framework of a composer in research project in the IMTR team at IRCAM. In this project we have experimented with different realtime processing techniques for the analysis, transformation, and resynthesis of particular morphological aspects of live performed voice and instrumental sounds. Based on segment-wise sound descriptions, the developed tools allow for re-orchestrating and re-organising particular morphological aspects of the live performer's sound using concatenative synthesis of pre-analysed sound materials driven by the real-time analysis. The relationship between the morphology of live performance and the synthesised sound materials is controlled by a set of compositional tools manipulating the extracted sound descriptions in real-time.
First Steps in Relaxed Real-Time Typo-Morphological Audio Analysis/Synthesis
This paper describes a real-time audio analysis/resynthesis system that we developed for a music piece for ensemble and electronics. The system combines real-time audio analysis and concatenative synthesis based on the segmentation of sound streams into constituting segments and the description of segments by an efficient set of descriptors adapted to the given musical context. The system has been implemented in Max/MSP using the FTM & Co and MuBu libraries and successfully employed in the production and performance of the piece. As more and more research in the domain of music information retrieval, we use the term of typo-morhpology to designate the description of sounds by morphologic criteria including the temporal evolution of sound features that also can provide pertinent means for the classification of sounds. Although, the article mainly insists on the technical aspects of the work, it occasionally contextualizes the different technical choices regarding particular musical aspects.
Using morphological description for generic sound retrieval
Systems for sound retrieval are usually “sourcecentred”. This means that retrieval is based on using the proper keywords that define or specify a sound source. Although this type of description is of great interest, it is very difficult to implement it into realistic automatic labelling systems because of the necessity of dealing with thousands of categories, hence with thousands of different sound models. Moreover, digitally synthesised or transformed sounds, which are frequently used in most of the contemporary popular music, have no identifiable sources. We propose a description framework, based on Schaeffer’s research on a generalised solfeggio which could be applied to any type of sounds. He defined some morphological description criteria, based on intrinsic perceptual qualities of sound, which doesn’t refer to the cause or the meaning of a sound. We describe more specifically experiments on automatic extraction of morphological descriptors.