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Granular synthesis is a flexible method to create a wide range of complex sounds, like the sound of rain or water, using very short waveforms, called grains. To synthesize realistic, natural sounds appropriate grains are needed. In an earlier paper we already presented a method to extract grains from recordings of complex sounds. In this paper we describe an extension of the earlier method in which the end of incomplete grains is estimated to improve sound quality. Additionally synthesis parameters that allow us to recreate sound output very close to the original recordings are found automatically. A few seconds of audio input will provide enough data to synthesize sounds of arbitrary length. The necessary grains only require little memory and since synthesis parameters can also be varied to change the nature of the sound, this method is especially beneficial for video games. While empirical listening suggests that the synthesized waveforms sound natural, a formal listening test was not conducted. Sound samples are provided.
Author (s): Siddiq, Sadjad
Affiliation:
Square Enix Co., Ltd., Tokyo, Japan
(See document for exact affiliation information.)
AES Convention: 142
Paper Number:9743
Publication Date:
2017-05-06
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Session subject:
Room Acoustics: Sound Field Simulation and Generation
Permalink: https://aes2.org/publications/elibrary-page/?id=18619
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Siddiq, Sadjad; 2017; Data-Driven Granular Synthesis [PDF]; Square Enix Co., Ltd., Tokyo, Japan; Paper 9743; Available from: https://aes2.org/publications/elibrary-page/?id=18619
Siddiq, Sadjad; Data-Driven Granular Synthesis [PDF]; Square Enix Co., Ltd., Tokyo, Japan; Paper 9743; 2017 Available: https://aes2.org/publications/elibrary-page/?id=18619