In this paper, the method for reconstructing FIR digital filter into ARMA direct form digital filter based upon adaptive ARMA Four Line Lattice filter with the phase estimation is proposed. The phase estimation is performed by the combination of GA (Genetic Algorithm) and SA (Simulated Annealing) in addition to the spectrum estimation. In order to reduce the calculation cost that will be significant issue for the system implementation of digital filters into the products, it will be necessary to design ARMA digital filter.Introducing the phase estimation method, it contributes the possibility to provide optimum ARMA digital filters that is not only relatively lower coefficient sensitivity and better robustness, but also it will maintain all its desired characteristics that include the phase performance. Maintaining the phase characteristics is the unforgettable factor for the fields of the inverse filtering problem for any opportunities. We conduct the original cost function that will cooperate with GA and SA searching in order to realize the phase estimation. In this paper, experimental results are also discussed to confirm the performance of proposed method.

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When listeners focus on a single frequency to detect an auditory signal, other unattended sounds are suppressed and sensitivity to those sounds is diminished. If they focus on a sound with two or more frequency components, similar results are obtained, but sensitivity to each of the components is less than to a single frequency. The present paper shows just how signal detection is degraded when attention is directed by multi-component cues (comprising either two or four tones) to targets at various frequencies. Psychometric functions obtained with the multi-component cues are shifted toward higher signal levels (signals are first detected at higher levels) relative to those obtained in control conditions with a single-component cue. As the cue components are spread further apart in frequency, the shift in the psychometric function may become as large as 3dB; nevertheless, it is a generally smaller than the shift for a signal frequency that does not match any frequency component of the cue. Frequency spacing among the cue components also affects detection, with performance better (smaller shifts in the psychometric function) when the components are very far apart than when moderately far apart.

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The production process of voiceless stop consonants was represented by a non-stationary autoregressive moving-average (ARMA) process, and the trajectories of poles and zeros from the noise burst to the following vowel were extracted from Japanese utterances of CV syllables containing voiceless stop consonants /p/, /t/, and /k/, using the SEARMA method. In order to clarify the relationship between the extracted parameters and the cues for perception of voiceless stop consonants, perceptual tests were conducted using synthetic CV syllables generated under various control conditions for these parameters. The relationship between the perceptual cues of voiceless stops and the acoustical parameters (i.e., the spectra and the duration of the consonantal noise, the orders of the model, the vocalic transition) were revealed.

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The noise fluctuation is very often measured in a quantized level form at a discrete time interval. By paying attention to this quantization procedure of the actual noise measurement, in this paper, a precise estimation method for the probability distribution form is proposed by using the roughly observed data with quantized levels. That is, we first introduce theoretically a general statistical orthonormal expression of the probability density function for the original noise level fluctuation of continuous level type before passing through the level quantization measurement mechanism. Based on this quantization mechanism and the averaging operation of statistical information, we propose a reasonable estimation method of the distribution parameters in the above statistical expression by using the statistical information on the roughly observed data. The original probability distribution form of the continuous noise level can be precisely estimated by substituting the estimated distribution parameters into the introduced probability expression of general type. On the basis of this estimation theory, a precise evaluation method for the L_x and L_eq noise evaluation indices is proposed. The effectiveness of the proposed method is confirmed experimentally too by applying it to first the simulation experiment and then the actual road traffic noise data.

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A comparison of the loudness of inside car noises from various sound sources in situations similar to daily life is investigated. If each sound is presented independently, subjects would pay more attention to the sound than in actual situations. In the present experiment, the impressions of the sounds while driving were judged continuously using the method of continuous judgment by category. This method makes it possible to evaluate the impressions of various noises without paying special attention to any of the specific noises in the same context and to examine the effect of each noise separately. The results suggest that some sounds tend to be overestimated compared with the background noises and others do not. The finding of this experiment may be helpful to find the effects of various factors in sound environments and take effective countermeasures.

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