This paper describes the results of subjective experiments investigating the characteristics of human phase perception. In these experiments, the stimuli have a flat amplitude spectrum and a group delay spectrum that has a single peak described by a Gaussian function where the mean (center frequency) and the standard deviation (bandwidth) are free parameters of interest. The first experiment was performed using stimuli with different peak values, where the center frequencies are fixed at 1,000 Hz and 4,000 Hz, and the bandwidths are also fixed. These bandwidths are computed by weighting the equivalent rectangular bandwidth (ERB) with certain parameters. It was found that when the peak values of the stimuli are between -1 ms and 2 ms, they are perceived to be zero phase, regardless of their center frequencies and bandwidths. Moreover, when the peak values of the stimuli are less than -8 ms or more than 10 ms and the bandwidths are less than 1 ERB, they are perceived to be similar. This result indicates that the nonzero-phase stimuli are similar when the bandwidth is less than 1 ERB. It was also found that the similarity of the stimuli reduces when the bandwidths of the nonzero-phase stimuli are more than 1 ERB.
The purpose of this paper is to shorten the analytical duration with keeping high resolution in frequency for the closed frequencies estimation. Existence of the closed frequencies in an input signal makes difficult the estimation with high resolution, because of a spectral leakage. It is difficult to eliminate the leakage. We utilize the leakage to estimate the closed frequencies without attempt to eliminate it. In general, the magnitude of leakage changes with the phase of an input signal. For changing the phase, an all-pass filter (APF) is used. This paper makes clear the relationships among three factors: the leakage, the phase, and the input frequencies (i.e., periodic components forming an input signal). The experimental results for estimating closed frequencies clearly show that the use of APF results in the duration shorter than 60% of the conventional methods with high resolution in frequency.
This paper describes a new method for objective evaluation of wind noise in the passenger compartment of a car. The perception of wind noise is affected by the masking effect by other noise and the particular source direction of the wind noise. Therefore, the human hearing properties of masking and sound localization should be taken into account when evaluating wind noise. The proposed evaluation method is based on these human hearing properties. The method can estimate the loudness and direction of noise in each frequency band by performing a masked frequency spectrum analysis and a cross correlation analysis based on a binaural signal processing model. Therefore, those wind noise components that are annoying to the passengers or those wind noise components whose source location can be determined by the human listener can be identified objectively. Furthermore, the total loudness of wind noise as determined by a jury of human listeners can be estimated quite precisely by adding the loudness of the frequency bands for noise emanating from the direction of the side window.
We applied the ultrasonic diffraction method for recognizing an acoustic structure of muscle tissue and diagnosising a structural change of the part of disease disturbance. However, in this signal processing application, the recognition accuracy depends on the accuracy of location of the focal plane. It is also necessary to estimate the location of the focal plane within short time. On the other hand, The MUSIC algorithm is high-resolution algorithm for estimating arrival direction of a sound sources. In this paper, we propose a method to estimate the acoustic focal point using the MUSIC algorithm at two points, then calculate the location of the focus based on these two estimates of the focal point.
Visualization of sound field helps us to intuitively understand mechanisms of various acoustic phenomena and therefore the technique is much effective for both of educational and engineering purposes. This paper presents some examples of sound field visualization based on numerical analysis. In order to analyze such complicated acoustic phenomena as reflection, diffraction and interference, the finite difference time domain (FDTD) method based on the wave theory is applied to the calculation. In the FDTD algorithm, all of the sound field is computed in discrete time steps and therefore transient acoustic phenomena can be easily animated. As an application of the numerical technique to environmental noise control engineering, sound reflection and diffraction around noise barriers with a variety of cross sectional shapes and noise propagation from depressed/semi-underground road structures are introduced in this paper.
This paper presents visualization of transient sound propagation in 2-dimensional room sound fields in which the typical shapes of concert halls are modeled by applying the finite difference time domain method. As a basic study on room acoustic design, sound propagation in rooms, scattering effect of acoustic diffusers and reflection characteristics of suspended panel arrays are investigated. Through the investigation, it has been confirmed that this kind of visualization technique is very effective to get intuitive comprehension of complex acoustic phenomena which occur in rooms. The technique can be useful tool for discussion on room and acoustic treatment between acoustic engineers and architects.
The Lamb wave inspection technique with a tire transducer has been used for the on-line defect inspection of steel sheets. However, the conventional Lamb wave inspection process has the following two problems. One is the existence of wide dead zones that appear in the near and far positions for the tire transducer. The other is misdetection due to parasitic echoes or electrical noises. Therefore, we have developed a method that could solve these problems using the two-dimensional signal characteristics. As a result, the dead zone and the misdetections can be reduced. This paper describes the measurement principle, the algorithm of the signal processing and the distinction logic. The results showed that the dead zone was reduced to 100 mm from the strip edge and the misdetection was eliminated.