In order to solve the problem of large error of delay estimation in low SNR environment, a new delay estimation method based on cross power spectral frequency domain weighting and spectrum subtraction is proposed. Through theoretical analysis and MATLAB simulation, among the four common weighting functions, it is proved that the cross-power spectral phase weighting method has a good sharpening effect on the peak value of the cross-correlation function, and it is verified that the improved spectral subtraction method generally has a good noise reduction effect under different SNR environments. Finally, the joint simulation results of the whole algorithm show that the combination of spectrum subtraction and crosspower spectrum phase method can effectively sharpen the peak value of cross-correlation function and improve the accuracy of time delay estimation in the low SNR environment. The results of this paper can provide useful help for sound source localization in complex environments.

Simultaneous perception of audio and visual stimuli often causes concealment or misrepresentation of information actually contained in these stimuli. Such effects are called the "image proximity effect" or the "ventriloquism effect" in the literature. Until recently, most research carried out to understand their nature was based on subjective assessments. The authors of this paper propose a methodology based on both subjective and objectively retrieved data. In this methodology, objective data reflect the screen areas that attract most attention. The data were collected and processed by an eye-gaze tracking system. To support the proposed methodology, two series of experiments were conducted - one with a commercial eye-gaze tracking system Tobii T60, and another with the Cyber-Eye system developed at the Multimedia Systems Department of the Gdańsk University of Technology. In most cases, the visual-auditory stimuli were presented using a 3D video. It was found that the eye-gaze tracking system did objectivize the results of experiments. Moreover, the tests revealed a strong correlation between the localization of a visual stimulus on which a participant's gaze focused and the value of the "image proximity effect". It was also proved that gaze tracking may be useful in experiments which aim at evaluation of the proximity effect when presented visual stimuli are stereoscopic.

The acoustic vector sensor (AVS) is used to measure the acoustic intensity, which gives the direction-ofarrival (DOA) of an acoustic source. However, while estimating the DOA from the measured acoustic intensity the finite microphone separation (d) in a practical AVS causes angular bias. Also, in the presence of noise there exists a trade off between the bias (strictly increasing function of d) and variance (strictly decreasing function of d) of the DOA estimate. In this paper, we propose a novel method for mitigating the angular bias caused due to finite microphone separation in an AVS. We have reduced the variance by increasing the microphone separation and then removed the bias with the proposed bias model. Our approach employs the finite element method (FEM) and curves fitting to model the angular bias in terms of microphone separations and frequency of a narrowband signal. Further, the bias correction algorithm based on the intensity spectrum has been proposed to improve the DOA estimation accuracy of a broadband signal. Simulation results demonstrate that the proposed bias correction scheme significantly reduces the angular bias and improves the root mean square angular error (RMSAE) in the presence of noise. Experiments have been performed in an acoustic full anechoic room to corroborate the effect of microphone separation on DOA estimation and the efficacy of the bias correction method.