This paper describes a prototype mechanical white noise generator has a source level of more than 170.0 dB (re 1µPa at 1 m) at the frequency range of 10 Hz to 100 kHz. The results of performance evaluation of the generator are as follows. The average source level of the generator measured by a step of 15°in horizontal (0 to 360。, 25 points) was 185.2 (SD (standard deviation): 2.3) dB (re 1µPa at 1 m). The maximum and minimum source levels were appeared at the frequency range of 2.5 to 5.0 kHz and around 100 kHz, respectively. The average source levels at 0°, 90。, 180。and 270° were 162.9 (SD: 10.6), 168.4 (SD: 10.0), 162.1 (SD: 9.1) and 166.5 (SD: 11.1) dB (re 1µPa at 1 m). The average source level measured by a step of 30° in vertical was 184.9 (SD: 2.2) dB (re 1µPa at 1 m). The relative maximum variation width of the source levels in horizontal and in vertical measurement were less than 7.0 dB and 1.0 dB, respectively.

In this study, we do research in a proper microphone arrangement method by way of evaluating and analyzing the relation between an open angle of the microphones and a time difference of an input sound signal for an exact definition of a sound source. Then, We can expect that existing robots or machines with an only vision system will have more excellent environmental adaptation ability by supports of hearing sense.

In this paper, we present a Sound Source Localization (SSL) based GCC (Generalized Cross Correlation)–PHAT (Phase Transform) and new measurement method of angle with robot auditory system for a network-based intelligent service robot. The main goal of this paper is to analysis performance of TDOA and GCC-PHAT sound source localization method and new angle measurement method is compared. We use GCC-PHAT for measuring time delays between several microphones. And sound source location is calculated by using time delays and new measurement method of angle. The robot platform used in this work is wever-R2, which is a network-based intelligent service robot developed at Intelligent Robot Research Division in ETRI.

A purpose of developing a sound source tracking system in this paper is to reduce the noise efficiently from the received signal by microphone array and measure the signal's time delay between the microphones. I have applied the wavelet analysis algorithm to the system and calculated the sound source's relative position For the performance evaluation, I have compared with the results of utilizing the digital filtering methods based on the FIR LPF using Kaiser window function and the inverse Chebyshev IIR LPF. As a result, I have confirmed the fact that 'time-scale' filter using inverse discrete wavelet transform was suitable for this system.

We have reported the new measurement system which was substituted digital filter for the analog filter in order to develop the optimal system that could find the time delay between each sensors with high accuracy. And also we have confirmed through the experiments that the accuracy of measurements were differentiated by the methods what kind of digital filter had been adopted. This paper suggests two algorithms which approximate the sound source's bearing and distance. One is that sound source's relative bearing can be approximately regarded as the gradient of hyperbolic asymptote, the other is that the source's range can be approximated under the condition of a long range source relative to the sensor's interval. And a series of experiments were carried out with the source's distance 22.42meters and the random bearing interval within the limits of -90˚~+90˚. As a result, we have recognized that the approximation methods could measure the bearing and distance with higher accuracy than the method using trigonometric relation could do.