SoundTracer workshop 2017: Olivier Lartillot
Channel: UniOslo_IMV
Date: 02/04/2018

Presentation on "Sound analysis for gestural interactions with large music dataset" at the SoundTracer workshop at the National Library of Norway 7 December 2017. 

The SoundTracer project requires to extract musical gestures from a large catalogue of folk music recordings. While melodic lines can be easily extracted from a cappella songs, the task is more challenging for other types of music such as Hardanger fiddle music. In such cases, we need to automatically transcribe the recordings and track melodic voices throughout the counterpoint of each composition. By segmenting melodic voices into phrases, we obtain a catalogue of candidate gestures. Other gestures can be obtained by performing a large range of audio and musical analysis of the recordings. The folk music catalogue is a large set of long recordings, each made of a succession of pieces of music that are highly disparate in terms of instrumentation. As no systematic metadata is associated with the catalogue, we are developping a method to automatically segment the songs into pieces and to classify based on instrumentation. I will also present the new SoundTracer app that enables you to draw a gesture in the air with your phone (currently only iPhone SE, 6S, 7, 8 or X) and to find pieces of music from the catalogue that is characterised by a similar musical gesture.

Olivier Lartillot is a researcher at the Department of Musicology at the University of Oslo, working in the fields of computational music and sound analysis and artificial intelligence. He designed MIRtoolbox, a referential tool for music feature extraction from audio. He also works on symbolic music analysis, notably on sequential pattern mining. In the context of his 5-year Academy of Finland research fellowship, he conceived the MiningSuite, an analytical framework that combines audio and symbolic research.