An integral equation with respect to sound pressure on the periphery of a given two-dimensional area was formulised to analyze two-dimensional sound field. For that purpose, the Hankel function of the second kind was used as a Green's function and applied to Green's theorem. The equation was rewritten in a matrix equation and then numerically calculated by dividing the periphery of two-dimensional area into N sections. The eigenvalue for a rectangle surrounded by a rigid wall was first obtained. The relation between the number of sections N and the accuracy of the calculation was shown. The calculation was also carried out for five kinds of shapes varying from a rectangle to a violin frame. On the basis of the eigenvalues calculated for the two-dimensional sound field isolated from outside, the acoustic significance of the shape of a violin frame was discussed.
The method of estimating the articulation of speech in the presence of a time-varying noise, whose sound levels are normally distributed, is studied on the basis of articulation index, and the estimated values are compared with the experimental results. If we assume that the level distribution of noise has the median L_<50>dB(A) and the standard deviation σdB(A), it is shown that the time-varying noise has an effect equivalent to steady noise of which level is larger by |a/2|σ^2 than L_<50> of the former, as far as the sound articulation is concerned. The value of the constant a is obtained as equal to -0. 112 from the experiment for steady noise. Thus the level of the steady noise equivalent to the time-varying noise is expressed as follows;L_s=L_<50>+0. 056σ^2. It is shown that this equivalent level corresponds well with the sound articulation obtained experimentally.
Speaker verification is the only method feasible for remote telephone handset user identification without resorting to additional input devices. Studies are made of speaker verification using the microphone input voice as the reference frame for speaker verification of an actual telephone voice. Various parameter sets as autocorrelation coefficients, linear prediction coefficients, PARCOR parameters, and log area ratio are evaluated for several analysis conditions in order to obtain the best parameter set and conditions. A score as high as 99. 8% is obtained with PARCOR parameters under the best analysis condition (see Table 4). Applying the above best parameter set and conditions to actual telephone voice verification directly, poor results of only 65% are obtained. Then a new idea involving average-self-inverse filtering has been proposed which normalizes the effect of linear distortion of actual telephone voice. The combined use of average-self inverse filtering and selected-band-analysis improves verification performance beyond that obtained with PARCOR parameters extracted directly from an actual telephone voice. Further improvement is possible by the additional use of pitch frequency for normalization of nonlinear distortions so that a better than 94% verification score is obtained.