For evaluating the output response fluctuation of the actual environmental acoustic system excited by arbitrary random inputs, it is important to predict a whole probability distribution form closely connected with many noise evaluation indexes Lx, Leq and so on. In this paper, a new type evaluation method is proposed by introducing lower and higher order type functional models matched to the prediction of the response probability distribution form especially from a problem-oriented viewpoint. Because of the non-negative property of the sound intensity variable, the response probability density function can be reasonably expressed in advance theoretically by a statistical Laguerre expansion series form. The system characteristic between input and output can be described by the regression relationship between the distribution parameters (containing expansion coefficients of this expression) and the stochastic input. These regression functions can be expressed in terms of the orthogonal series expansion. Since, in the actual environment, the observed output is inevitably contaminated by the background noise, the above regression functions can not be directly employed as the models for the actual environment. Fortunately, the observed output can be given by the sum of the system output and the background noise on the basis of additivity of intensity quantity and the statistical moments of the background noise can be obtained in advance. So, the models relating the regression functions to the function of the observed output can be derived. Next, the parameters of the regression functions are determined based on the least-squares error criteria and the measure of statistical independency according to the level of non-Gaussian property of the function of the observed output. Thus, by using the regression functions obtained by the proposed identification method, the probability distribution of the output reducing the background noise can be predicted. Finally, the effectiveness of the proposed method is confirmed experimentally too by applying it to an actual indoor-outdoor acoustic system.

This paper shows how a divisive state clustering algorithm that generates acoustic Hidden Markov models (HMM) can benefit from a tied-mixture representation of the probability density function (pdf) of a state and increase the recognition performance. Popular decision tree based clustering algorithms, like for example the Successive State Splitting algorithm (SSS) make use of a simplification when clustering data. They represent a state using a single Gaussian pdf. We show that this approximation of the true pdf by a single Gaussian is too coarse, for example a single Gaussian cannot represent the differences in the symmetric parts of the pdf's of the new hypothetical states generated when evaluating the state split gain (which will determine the state split). The use of more sophisticated representations would lead to intractable computational problems that we solve by using a tied-mixture pdf representation. Additionally, we constrain the codebook to be immutable during the split. Between state splits, this constraint is relaxed and the codebook is updated. In this paper, we thus propose an extension to the SSS algorithm, the so-called Tied-mixture Successive State Splitting algorithm (TM-SSS). TM-SSS shows up to about 31% error reduction in comparison with Maximum-Likelihood Successive State Split algorithm (ML-SSS) for a word recognition experiment.

Photoacoustic spectroscopy (PAS) has recently received much attention especially for plant photosynthesis research, because this technique is capable of performing non-destructive measurement without any pre-treatment of specimens. So far we have developed a PAS system equipped with an open photoacoustic cell (OPC), which allows in situ and in vivo measurements of plant photosynthesis of intact undetached leaves. In this study, we have measured photosynthesis reaction using OPC and developed a Confocal Scanning Photoacoustic Microscopy (CSPAM) system, in which PAS is combined with confocal scanning laser microscopy. The system allows simultaneous measurement of acoustic signal and another signal such as fluorescence, and also gives two- and three- dimensional intensity distributions of these signals, thereby giving two- and three- dimensional information about photosynthetic activity of plants.

Characteristics of an FBG hydrophone are described under various conditions. The developed FBG hydrophone detects an acoustic field in water with good performances: linear response,high sensitivity,high stability,wide dynamic range as large as 90 dB and wide operation frequency range from a few kHz to a few MHz. A WDM FBG hydrophone consisting of two FBGs in serial connection can detect simultaneously amplitudes and phases of acoustic fields at different points,which in turn allows a directive measurement of an acoustic field in water.

This paper introduces an acoustic echo canceller system materialized with a 16-bit fixed point processing type DSP (Analog Devices, ADSP-2181). This experimental system uses the tri-quantized-x individually normalized least mean square (INLMS) algorithm little degrading the convergence property under the fixed point processing. The experimental system also applies a small step gain to the algorithm to prevent the double-talk from increasing the estimation error. Such a small step gain naturally reduces the convergence speed. The experimental system compensates the reduction by applying the block length adjustment technique to the algorithm. This technique enables to ceaselessly update the coefficients of the adaptive filter even when the reference signal power is low. The experimental system thus keeps the echo return loss enhancement (ERLE) high against the double-talk.

An Acoustic echo canceller has problems adaptating under noisy or double-talk conditions. The adaptation process requires a precise identification of the temporarily changed room impulse response. To do this, both minimizing the step size parameter of the Least Mean Square (LMS) method to be as small as possible and giving up on updating the adaptive filter coefficients have been considered. This paper describes an adaptive cross-spectral technique that is robust to adaptive filtering under noisy or double-talk conditions and for colored signals such a speech signal. The cross-spectral technique was originally developed to measure the impulse response in a linear system. Here we apply in the adaptive cross-spectral technique to solve the acoustic echo cancelling problem. This cross-spectral technique takes the ensemble average of the cross spectrum between input and error signals and the averaged cross spectrum is divided by the averaged power spectrum of the input signal to update the filter coefficients. We have confirmed that the echo signal is suppressed by about 15 dB even under double-talk conditions. We also explain that this method has a systematic error due to using a short time block for estimating the room impulse response. Then we investigate overlapping every last half block by the following first half block in order to reduce the effect of the systematic error. Finally, we compare our method with the Frequency-domain Block LMS (FBLMS) method because both methods are implemented in the frequency domain using a short time block.

In this paper, we propose an adaptive lattice-transversal joint (LTJ) filter structure that is quite suitable for the practical implementation of the acoustic echo canceller. The structure maintains fast convergence of the lattice structure and low computational complexity of the transversal structure simultaneously. It is particularly more efficient in memory usage than any other existing fast-convergent algorithm for the acoustic echo cancellation.

This paper presents both new analytical and new numerical solutions to the problem of generating waveforms exhibiting a low peak-to-peak factor. One important application of these results is in the generation of pseudo-white noise signals that are commonly uses in multi-frequency measurements. These measurements often require maximum signal-to-noise ratio while maintaining the lowest peak-to-peak excursion. The new synthesis scheme introduced in this paper uses the Discrete Fourier Transform (DFT) to generate pseudo-white noise sequence that theoretically has a minimized peak-to-peak factor, Fp-p. Unlike theoretical works in the literature, the method presented here is based in purely discrete mathematics, and hence is directly applicable to the digital synthesis of signals. With this method the shape of the signal can be controlled with about N parameters given N harmonic components. A different permutation of the same set of offset phases of the "source harmonics" creates an entirely different sequence.

An acoustic diagnosis technique for the blower by wavelet transform and neural networks is described. It is important for this diagnosis to detect surging phenomena, which lead to the destruction of the blower. Dyadic wavelet transform is used as the pre-processing method. A multi-layered neural network is used as the discrimination method. Experiment is performed for a blower. The results show that the neural network with wavelet transform can detect surging sound well.

In the measurement of actual random phenomenon, the observed data often contain the fuzziness due to the existence of confidence limitation in measuring instruments, permissible error in experimental data, some practical simplification of evaluation procedure and a quantized error in digitized observation. In this study, by introducing the well-known fuzzy theory, a state estimation method based on the above fuzzy observations is theoretically proposed through an establishment of wide sense digital filter under the actual situation of existence of the background noise in close connection of the inverse problem. The validity and effectiveness of the proposed method are experimentally confirmed by applying it to the actual fuzzy data observed in an acoustic environment.

This paper describes a novel image reconstruction algorithm and experimental results of a 3-dimensional acoustical holographic imaging system which has a limited number of transducers distributed sparsely. The proposed algorithm is based on the conjugate gradient projection onto convex sets (CGPOCS), which allows the addition of convex sets constrained by a priori information to reduce ambiguity and extract resolution iteratively. By several experiments, it is proven that the concept of the new 3-D acoustic image reconstruction algorithm has following improvements:1. the artifacts caused by the spurious lobes can be reduced under the condition that the inter-spacing of elements is larger than the wave length,2. the instability caused by the lack of information about the actual point spread function (PSF) can be reduced,3. the actual PSF can be estimated concurrently with during the image reconstruction process.

The objective of this paper is to find a parametric representation for the vocal-tract log-area function that is directly and simply related to basic acoustic characteristics of the human vocal-tract. The importance of this representation is associated with the solution of the articulatory-to-acoustic inverse problem, where a simple mapping from the articulatory space onto the acoustic space can be very useful. The method is as follows: Firstly, given a corpus of log-area functions, a parametric model is derived following a factor analysis technique. After that, the articulatory space, defined by the parametric model, is filled with approximately uniformly distributed points, and the corresponding first three formant frequencies are calculated. These formants define an acoustic space onto which the articulatory space maps. In the next step, an independent component analysis technique is used to determine acoustic and articulatory coordinate systems whose components are as independent as possible. Finally, using singular value decomposition, acoustic and articulatory coordinate systems are rotated so that each of the first three components of the articulatory space has major influence on one, and only one, component of the acoustic space. An example showing how the proposed model can be applied to the solution of the articulatory-to-acoustic inverse problem is given at the end of the paper.

When we use a telephone-handset, the frequency response of the telephone-earphone becomes degraded because of the leak through the slit between the ear and the earphone. Consequently, it is very important to establish the design method of the telephone-handset which reduces the effect of leak. No one has tried to design the telephone-handset to reduce the effect. We are the only ones to have proposed an automatic design method by nonlinear optimization techniques. However, this method gives only one set of the acoustic parameters aiming at a certain specific target frequency response, and therefore lacks flexibility in the actual design problem. On the other hand, the design method proposed in this paper, which uses Monte-Carlo method, gives an infinite number of sets of acoustic parameters that realize infinite frequency responses within the target allowable region. As these infinite number of sets become directly the design ranges of acoustic parameters, the proposed method has the flexibility that any set of the acoustic parameters belonging to the design ranges guarantees the corresponding response to be within the target allowable region, and at the same time reduces the effect of leak. This flexibility is advantageous to the actual design problem.

This paper describes a new and realisable speech enhancement structure which simulates the cocktail party effect with a modified iterative Wiener filter and a multi-layer perceptron neural network. The key idea is to use the neural network as a speaker recognition system to govern the iterative Wiener filter. The neural network is a modified perceptron with a hidden layer using feature date extracted from LPC cepstral analysis. The proposed technique has been successfully used for speech enhancement when the interference is competing speech or broad band noise.

We proposed a new thchnique using saw wave modulation light to measure the thermal diffusivity of a transparent adhesive by photoacoustic microscope. In this technique, the time required for the measurement of it can be reduced by one-fifth compared with that of a conventional method.

Based on the test method proposed by Sub-Committee G of the International Special Committee on Radio Interference, most telephone receivers in Japan have insufficient immunity to acoustic noise caused by radio-frequency fields. This is because the modulation depth of the RF signal used is too high to accurately simulate the audio-frequency components of TV video signals. Reducing the modulation depth from 80% to 5% produces a more realistic simulation.

A microphone array system with multi-stage processing for speech enhancement is presented in this paper. Two beamformers with uniform directional patterns, one aimed at the target source and the other at the interfering sources, convert the multi-channel inputs into two data sequences. A novel microphone array structure with a small aperture has been designed to obtain the dual beamformers. The outputs of the two beam-formers are then presented to a post-processing stage to further improve the quality and intelligibility of the speech signal. The post-processing stage can be selected from one of three different algorithms that are presented, which are suitable for different acoustic environments. Applications for such a system include hands-free telephony, teleconferencing and also special situations where speech signals must be picked up in an extremely noisy acoustic environment in which the microphones are hidden (e.g. in a forensic covert recording system).

A new electron-beam wafer inspection system has been developed. The system has a resolution of 5 nm or better, and is applicable to quarter-micron devices such as 256 Mbit DRAMs. The most remarkable feature of this system is that a specimen stage is built in the objective lens and allows a working distance (WD) of 0. "WD=0"minimizes the effect of lens aberrations, and maximizes the resolving power. Innovative designs to achieve WD=0 are as follows: (1)A large objective lens of 730-mm width 730-mm depth 620-mm height that serves as a specimen chamber, has been developed. (2)A hollow specimen stage made of non-magnetic materials has been developed.It allows the lower pole piece and magnetic coile of the objective lens inside it. (3)Acoustic motors made of non-magnetic materials are em-ployed for use in vacuum.

In order to ensure the reliability and safety of equipment installed in process lines, it is important that maintenance and management should make efficient use of machine diagnosis techniques. Machine diagnosis by means of acoustic signals has hitherto been beset with difficulty, but there is now a strong demand that new acoustic type diagnosis equipment (utilizing acoustic signals) be developed. In response to this demand, the authors recently conducted research on diagnosis of machine faults by means of the processing of acoustic signals. In this research they were able to develop new acoustic type machine diagnosis techniques, and, using these techniques, to develop acoustic diagnosis equipment for practical use.

Ultrasonic diffraction image of specimen informs its acoustic structure as X ray diffraction method for analysis of the crystal structure. This ultrasonic diffraction method has a feature that focused ultrasound beam is used and diffraction image is observed on focal plane. When the structure of specimen is perfectly periodic, its diffraction image produces symmetrical respect to origin, but the diffraction image of weak periodic structure such as living tissue has some asymmetricity. In this paper, the principle of ultrasonic diffraction method, and data processing for asymmetrical and scattered diffraction image caused by weak periodic structure are described. The results of diffraction image of plant tissue and animal tissue, and its discussion are also described. This method is expected to be useful in evaluation of acoustic structure such as living tissue and internal tissue of bone.