This paper presents a system for controlling the sound spatialization of a live performance by means of the acoustic localization of the performer. Our proposal is to allow a performer to directly control the position of a sound played back through a spatialization system, by moving the sound produced by its own musical instrument. The proposed system is able to locate and track the position of a sounding object (e.g., voice, instrument, sounding mobile device) in a two-dimensional space with accuracy, by means of a microphone array. We consider an approach based on Generalized Cross-Correlation (GCC) and Phase Transform (PHAT) weighting for the Time Difference Of Arrival (TDOA) estimation between the microphones. Besides, a Kalman filter is applied to smooth the time series of observed TDOAs, in order to obtain a more robust and accurate estimate of the position. To test the system control in real-world and to validate its usability, we developed a hardware/software prototype, composed by an array of three microphones and a Max/MSP external object for the sound localization task. We have got some preliminary successfully results with a human voice in real moderately reverberant and noisy environment and a binaural spatialization system for headphone listening. © 2011 Daniele Salvati et al.
Sound spatialization control by means of acoustic source localization system
Salvati D.;
2011-01-01
Abstract
This paper presents a system for controlling the sound spatialization of a live performance by means of the acoustic localization of the performer. Our proposal is to allow a performer to directly control the position of a sound played back through a spatialization system, by moving the sound produced by its own musical instrument. The proposed system is able to locate and track the position of a sounding object (e.g., voice, instrument, sounding mobile device) in a two-dimensional space with accuracy, by means of a microphone array. We consider an approach based on Generalized Cross-Correlation (GCC) and Phase Transform (PHAT) weighting for the Time Difference Of Arrival (TDOA) estimation between the microphones. Besides, a Kalman filter is applied to smooth the time series of observed TDOAs, in order to obtain a more robust and accurate estimate of the position. To test the system control in real-world and to validate its usability, we developed a hardware/software prototype, composed by an array of three microphones and a Max/MSP external object for the sound localization task. We have got some preliminary successfully results with a human voice in real moderately reverberant and noisy environment and a binaural spatialization system for headphone listening. © 2011 Daniele Salvati et al.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.