Vibro-acoustic coupling between plate vibrations and the sound field inside a cylindrical structure is investigated. Each end plate of the cylindrical structure is excited by a point force. When the excitation position, which directly affects the vibration characteristics of the plates, is examined by shifting the point of application radially along the plate, the sound field is estimated based on the contribution defined as the ratio of acoustic energy stored in each acoustic mode to the total acoustic energy in the entire sound field. Coupling is intensified by the coincidence of a circumferential order with respect to the modes of plate vibration and of the sound field. Therefore, if the vibration modes at the two end plates have different orders due to the influence of the excitation position, then the sound field is composed of a number of acoustic modes. In particular, excitation at a position near the greatest flexural displacement causes the vibration energy to increase, and the contribution of the corresponding acoustic mode also increases. However, approaching the nodal circle of plate vibration, the excitation position develops coupling solely with the other plate vibration, because the occurrence of the vibration mode is restrained.

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In this paper, we describe a new source separation method in which uses spatial information derived from the direction of arrival (DOA) estimates of each direct and reflected sound issued. The method we propose has the following steps: (1) each DOA is estimated using matching pursuit and reoptimized after each new DOA is estimated, (2) using these DOA estimates, the mixing matrix is also estimated and the inverse of the mixing matrix is used to separate the mixture signals. In our experiments, we obtained a better signal separation with the new method than with the conventional frequency-domain independent component analysis (ICA)-based source separation method.

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This paper describes the problem caused by near-field sound sources. Formerly, the authors proposed a 2-ch passive subtractive beamformer with a single sharp notch for noise reduction. It is obvious that the single sharp notch is insufficient for dealing with near-field, non-point sound sources. To solve this problem, this paper presents the hybrid subtractive beamformer that is realized as a cascade connection of single subtractive beamformers. The number of connections depends on frequency to minimize the negative effect caused by spatial aliasing when an objective signal is assumed as a wide-band speech signal. The experimental results verifies that the hybrid beamformer has an advantage in reducing signal distortion over the original single subtractive beamformer.

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The conventional model of the linear prediction analysis suffers from difficulties in estimating vocal tract characteristics of high-pitched speakers. This is because the autocorrelation function used by the autocorrelation method of linear prediction for estimating autoregressive coefficients is actually an “aliased” version of that of the vocal tract impulse response. This “aliasing” occurs due to the periodic nature of voiced speech. Generally it is accepted that homomorphic filtering can be used to obtain an estimate of vocal tract impulse response which is free from periodicity. Thus linear prediction of the resulting vocal tract impulse response (referred to as homomorphic prediction) is expected to be free from variations of fundamental frequencies. To our knowledge any experimental study, however, has not yet appeared on the suitability of this method for analyzing high-pitched speech. This paper presents a detail study on the prospects of homomorphic prediction as a formant tracking tool especially for high-pitched speech where linear prediction fails to obtain accurate estimation. The formant frequencies estimated using the proposed method are found to be accurate by more than an order of magnitude compared to the conventional procedure. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch periods covering typical male and high-pitched female speakers. The validity of the proposed method is also examined by inspecting the spectral envelopes of natural speech spoken by high-pitched female speakers. We noticed that almost all the previous methods dealing with this limitation of linear prediction are based on the covariance technique where the obtained AR filter can be unstable. The solutions obtained by the current method are guaranteed to be stable which makes it superior for many speech analysis applications.

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In this paper the blind separation of speech signals from their convoluted mixtures using frequency domain fixed-point independent component analysis algorithm, based on negentropy maximization, is presented. We also discuss fundamental problems of fixed-point ICA by negentropy maximization arising in the separation of the speech signal due to disobedience of the Central Limit Theorem (CLT) by the mixed speech data in the frequency domain. The experimental evidences show that CLT failure is happening due to the spectral sparseness of sources. We also present a blind method to mitigate the negative effects of this by combining null beamforming with the ICA. This combination gives a good result under the low reverberation conditions.

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