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Descriptor driven concatenative synthesis tool for Python

Abstract

A command-line tool and Python framework is proposed for the exploration of a new form of audio synthesis known as ‘concatenative synthesis’, a form of synthesis that uses perceptual audio analyses to arrange small segments of audio based on their characteristics. The tool is designed to synthesise representations of an input target sound using a source database of sounds. This involves the segmentation and analysis of both the input sound and database, the matching of input segments to their closest segment from the database, and the resynthesis of the closest matches to produce the final result. The project aims to provide a tool capable of generating high-quality sonic representations of an input, to present a variety of examples that demonstrated the breadth of possibilities that this style of synthesis has to offer and to provide a robust framework on which concatenative synthesis projects can be developed easily. The purpose of this project was primarily to highlight the potential for further development in the area of concatenative synthesis, and to provide a simple and intuitive tool that could be used by composers for sound design and experimentation. The breadth of possibilities for creating new sounds offered by this method of synthesis makes it ideal for digital sound design and electroacoustic composition. Results demonstrate the wide variety of sounds that can be produced using this method of synthesis. A number of technical issues are outlined that impeded the overall quality of results and efficiency of the software. However, the project clearly demonstrates the strong potential for this type of synthesis to be used for creative purposes.

Keywords

Concatenative synthesis; Python; audio descriptor; audio analysis; command line tool; Python framework; Python sound;

How to Cite

Perry, S., (2017) “Descriptor driven concatenative synthesis tool for Python”, Fields: journal of Huddersfield student research 3(1). doi: https://doi.org/10.5920/fields.2017.12

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Authors

Sam Perry

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Creative Commons Attribution 4.0

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