Localization of multiple sound sources based on a CSP analysis with a microphone array

Abstract

Accurate localization of multiple sound sources is indispensable for the microphone array-based high quality sound capture. For single sound source localization, the CSP (Cross-power Spectrum Phase analysis) method has been proposed. The CSP method localizes a sound source as a crossing point of sound directions estimated using dierent microphone pairs. However, when localizing multiple sound sources, the CSP method has a problem that the localization accuracy is degraded due to cross-correlation among dierent sound sources. To solve this problem, this paper proposes a new method which suppresses the undesired cross-correlation by synchronous addition of CSP coecients derived from multiple microphone pairs. Experiment results in a real room showed that the proposed method improves the localization accuracy when increasing the number of the synchronous addition.

Multiple Frequency and Source Angle Estimation by Gaussian Mixture Model with Modified Microphone Array Data Model

“…The sampling frequency was thus 192 kHz, the spacing of microphone elements was 5 cm and speed of sound was assumed to be 340 m/s. Three other methods were tested for comparison: the generalized cross-correlation phase transform (GCC-PHAT) [2], the conventional CSS method [7] and a modification of the total least-squares CSS method (CSS-MTLS) [8]. For the proposed method, 218 frequency bins were utilized in the range from • .…”

“…The main factors reducing the efficiency of source localization in navigation systems are background noise, multiple source locations, and variation in the sound patterns and source frequencies [1]. A number of methods have been introduced in order to improve the source localization efficiency, including, time-difference-of-arrival (TDOA)-based DOA estimation [2], delay and sum beamforming [3] and subspace method [4]- [6].…”

Multichannel speech separation and localization by frequency assignment

“…Brandstein and colleagues proposed a method that uses the time difference of arrival of the speech to estimate the position of the sound source in three-dimensional space [18]. In contrast to these methods having a single speaker, Nishiura and colleagues proposed a sound source localization method for multiple speakers [23]. Although these methods are effective, they are restricted to a single speaker or in two-dimensional space.…”

“…Recently, a great deal of research has addressed sound source localization by using microphone arrays [18][19][20][21][22][23]. The understanding of the spatial position of sound is used in noise reduction, sound source tracking, and speech emphasis.…”

Source localization for multiple speech sources using low complexity non-parametric source separation and clustering

“…Other methods to solve the multiple intersection point problem include methods based on clustering of intersection points and correlation of signals [11,12]. Figure 1 shows the problem when intersecting DOA estimates for localiza- …”