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Chengxiang LU Takayoshi NAKAI Hisayoshi SUZUKI
In order to describe the flow passing through the glottis, we constructed a dynamic three-dimensional finite element model of the human larynx. The transient flow fields in the laryngeal model were calculated to examine the dynamic effects generated by the vocal fold vibration. A phase difference between the upper and lower edges of the vocal folds was included in the model to investigate the effect of the glottal shapes on pressure-flow relationships in the larynx during the vocal fold vibration. Using STAR-CD thermofluids analysis system, which is capable of treating the transient flow in moving-boundary situations with finite volume method, we solved the viscous incompressible Navier-Stokes equations to investigate the glottal flows and transglottal pressures as a function of the vocal fold vibration. The results were compared to the uniform glottis model and the theoretical model proposed by Ishizaka and Matsudaira, respectively. The effects of dynamic factors on the pressure distributions and flow patterns in the larynx resulting from the vocal-fold vibration were also discussed.
Hiroyuki HATANO Masahiro FUJII Atsushi ITO Yu WATANABE Yusuke YOSHIDA Takayoshi NAKAI
We focus on forward-looking radar network systems for automotive usages. By using multiple radars, the radar network systems will achieve reliable detection and wide observation area. The forward-looking systems by cameras are famous. In order to realize more reliable safety, the cameras had better be used with other sensing devices such as the radar network. In the radar network, processing of the data, which is derived from the multiple receivers, is important because the processing decides the estimation performance. In this paper, we will introduce our estimation algorithm which focuses on target existence probability and virtual receivers. The performance will be evaluated by simulated targets which are both single point model and 3D target model.
Chengxiang LU Takayoshi NAKAI Hisayoshi SUZUKI
This paper describes an implementation of the finite element method to examine the effects of actual lip shape on the sound radiation. A three-dimensional finite element approach by Galerkin method was used. The accuracy of the calculation of finite element method for the sound radiation was tested by comparing it with the exact solutions for a circular piston radiator on an infinite baffle. Using a set of finite element models of the vocal tract, we calculated the responses to a pure tone input and the sound fields over the frequency range of 100 Hz-7 kHz. The transfer functions are examined in detail for vowels /a/ and /i/ when the shape of the actual lips is simplified as a planeradiation surface. The effects of lip shape on the distribution of sound pressures are also shown in both the vocal tract and the surrounding space of the mouth opening.
The estimation of the power spectral density (PSD) of noise is crucial for retrieving speech in noisy environments. In this study, we propose a novel method for estimating the non-white noise PSD from noisy speech on the basis of a generalized gamma distribution and the minimum mean square error (MMSE) approach. Because of the highly non-stationary nature of speech, deriving its actual spectral probability density function (PDF) using conventional modeling techniques is difficult. On the other hand, spectral components of noise are more stationary than those of speech and can be represented more accurately by a generalized gamma PDF. The generalized gamma PDF can be adapted to optimally match the actual distribution of the noise spectral amplitudes observed at each frequency bin utilizing two real-time updated parameters, which are calculated in each frame based on the moment matching method. The MMSE noise PSD estimator is derived on the basis of the generalized gamma PDF and Gaussian PDF models for noise and speech spectral amplitudes, respectively. Combined with an improved Weiner filter, the proposed noise PSD estimate method exhibits the best performance compared with the minimum statistics, weighted noise estimation, and MMSE-based noise PSD estimation methods in terms of both subjective and objective measures.