This paper describes the implementation of an innovative musical interface based on the sound localization capability of a microphone array. Our proposal is to allow a musician to plan and conduct the expressivity of a performance, by controlling in realtime an audio processing module through the spatial movement of a sound source, i.e. voice, traditional musical instruments, sounding mobile devices. The proposed interface is able to locate and track the sound in a two-dimensional space with accuracy, so that the x-y coordinates of the sound source can be used to control the processing parameters. In particular, the paper is focused on the localization and tracking of harmonic sound sources in real moderate reverberant and noisy environment. To this purpose, we designed a system based on adaptive parameterized Generalized Cross-Correlation (GCC) and Phase Transform (PHAT) weighting with Zero-Crossing Rate (ZCR) threshold, a Wiener filter to improve the Signal to Noise Ratio (SNR) and a Kalman filter to make the position estimation more robust and accurate. We developed a Max/MSP external objects to test the system in a real scenario and to validate its usability.

A sound localization based interface for real-time control of audio processing

Salvati D.;
2011-01-01

Abstract

This paper describes the implementation of an innovative musical interface based on the sound localization capability of a microphone array. Our proposal is to allow a musician to plan and conduct the expressivity of a performance, by controlling in realtime an audio processing module through the spatial movement of a sound source, i.e. voice, traditional musical instruments, sounding mobile devices. The proposed interface is able to locate and track the sound in a two-dimensional space with accuracy, so that the x-y coordinates of the sound source can be used to control the processing parameters. In particular, the paper is focused on the localization and tracking of harmonic sound sources in real moderate reverberant and noisy environment. To this purpose, we designed a system based on adaptive parameterized Generalized Cross-Correlation (GCC) and Phase Transform (PHAT) weighting with Zero-Crossing Rate (ZCR) threshold, a Wiener filter to improve the Signal to Noise Ratio (SNR) and a Kalman filter to make the position estimation more robust and accurate. We developed a Max/MSP external objects to test the system in a real scenario and to validate its usability.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1189775
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