A pilot study on augmented speech communication based on Electro-Magnetic Articulography

Speech is the most natural form of communication for human beings. However, in situations where audio speech is not available because of disability or adverse environmental condition, people may resort to alternative methods such as augmented speech, that is, audio speech supplemented or replaced by other modalities, such as audiovisual speech, or Cued Speech. This article introduces augmented speech communication based on Electro-Magnetic Articulography (EMA). Movements of the tongue, lips, and jaw are tracked by EMA and are used as features to create hidden Markov models (HMMs). In addition, automatic phoneme recognition experiments are conducted to examine the possibility of recognizing speech only from articulation, that is, without any audio information. The results obtained are promising, which confirm that phonetic features characterizing articulation are as discriminating as those characterizing acoustics (except for voicing). This article also describes experiments conducted in noisy environments using fused audio and EMA parameters. It has been observed that when EMA parameters are fused with noisy audio speech, the recognition rate increases significantly as compared with using noisy audio speech only.     

An analysis of expression data using a support vector machine and dimensional reduction methods

Gene expression data are expected to be a significant aid in the development of efficient cancer diagnosis and classification platforms. However, gene expression data are high-dimensional and the number of samples is small in comparison to the dimensions of the data. Furthermore, the data are inherently noisy. Therefore, in order to improve the accuracy of the classifiers, we would be better off reducing the dimensionality of the data. As a method of dimensionality reduction, there are two previous proposals: feature selection and dimensionality reduction. Feature selection is a feedback method which incorporate the classifier algorithm in the future selection process. Dimensionality reduction refers to algorithms and techniques which create new attributes as combinations of the original attributes in order to reduce the dimensionality of a data set. In this article, we compared the feature selection methods and the dimensionality reduction methods, and verified the effectiveness of both types. For the feature selection methods we used one previously known method and three proposed methods, and for the dimensionality reduction methods we used one previously known method and one proposed method. From an experiment using a benchmark data set, we confirmed the effectiveness of our proposed method with each type of dimensional reduction method.     

Anisotropic thermal conductivity of three-layer laminated carbon-graphite composites from carbonized wood

Composites with characteristics of anisotropic thermal conductivity for thermal management in Solar Power Satellite (SPS), to discharge the heat that was generated when solar energy was not converted to electricity, were developed by alternating layers of laminated graphite and carbonized wood. The effects of the weight fraction of carbonized wood, particle size, interlayer interfaces, and environment temperature on the thermal conductivity and the ratio of thermal conductivity between horizontal and vertical directions (H/V ratio) to the plain surface of samples were discussed. The thermal conductivities of carbon–graphite (C/G) composites were measured using the laser flash method. Laminated C/G composites improved the anisotropic thermal conductivity. The highest H/V ratio of 10.17 was obtained at 10 wt% of carbonized wood. Particle size and interlayer interfaces were found to affect the anisotropic thermal conductivity. The thermal conductivity of C/G composites increased with increasing temperature from 25 °C to 150 °C.     

Technologies to improve photo-sensitivity and reduce VOD shuttervoltage for CCD image sensors

New technologies to increase the photo-sensitivity and reduce the shutter voltage of the vertical over-flow-drain (VOD) have been developed for CCD image sensors. The photo-sensitivity was increased 40% by forming an anti-reflection film over the photodiode and reducing the thickness of the p⁺-layer formed at the photodiode surface. The VOD shutter voltage was reduced from 31 to 18 V by using an epitaxially grown substrate with double impurity concentration layers     

Characteristics of VHF excited hydrogen plasmas using a ladder-shaped electrode

A VHF excited hydrogen plasma was produced with a ladder-shaped electrode whose excitation frequency ranged up to 100 MHz for gas pressures of 40–200 mTorr and the plasma parameters were measured with a Langmuir probe. When the excitation frequency was increased, the electron density increased and the electron temperature decreased. The pressure dependence of the electron temperature at excitation frequencies of 65 and 100 MHz was different from the usual relationship: the electron temperature tended to increase with increasing pressure.     

Discrete–variational Xα calculations of graphite and alkali–metal graphite intercalation compounds

First-principles molecular orbital calculations using discrete–variational (DV)-Xα method are carried out on the model clusters of graphite and alkali–metal graphite intercalation compounds MC_x(M=Li, Na, K, Rb, and Cs). Results of the calculations are used so as to simulate the experimentally observed near-edge X-ray-absorption fine-structures (XANES) and ultraviolet photoelectron spectra. For the clusters of graphite and KC_x, the calculated partial electronic densities of states (PDOSs) are in good agreement with the experimental C K-edge and K K-edge XANES spectra, respectively. Furthermore, the accordance between the calculated DOSs and the observed UPS spectra of graphite and RbC_x is also satisfactory. It is shown that the Fermi level is pushed up into the conduction band of graphite by doping alkali metals.     

High-Index-Layer Coating on a Lensed Fiber Endface for Enhanced Focusing Power

A new scheme for lensed fibers with a high focusing power is proposed. The new lensed fiber has a high-index layer coated (HILC) on a convex-shaped endface of a single-mode fiber (SMF). Numerical investigation shows that, by coating a 10-mum-thick film with refractive index of 3.7, the lensed fiber can contract the beam diameter of the propagating mode from 10.4 mum at the wavelength of 1.55 mum, to 1.2 mum. The enhanced focusing effect of the lensed fiber has been confirmed experimentally by coating an a-Si:H film on the lensed endface. The measured focused spot diameter was as small as 1.6 mum, much the same as the wavelength.     

Evaluation of TaqMan PCR assay for detecting Salmonella in raw meat and shrimp.

We evaluated the TaqMan Salmonella amplification/detection kit from PE Applied Biosystems, which uses a polymerase chain reaction (PCR) assay for rapid detection of Salmonella in food samples. This system uses the 5' nuclease activity of Taq DNA polymerase, which digests an internal fluorogenic probe to monitor the amplification of the target gene. The system's sensitivity and specificity were evaluated using 42 serotypes of 68 Salmonella strains isolated from fecal samples from patients in Tokyo, Japan, and 39 non-Salmonella strains in 22 genera. There were no false-negative or false-positive results. This PCR assay can detect 3 CFU per PCR tube of Salmonella in pure culture (120 CFU/ml of TSB culture). PCR signals were attenuated with artificially contaminated shrimp, but a similar detection limit was obtained. TaqMan's performance was tested with 100 meat and chicken samples purchased from stores in Tokyo. Overall, two of the DNA extraction protocols (the Chelex and EnviroAmp methods) worked equally well, with some exceptions. Of the 100 samples analyzed, 10 were positive for Salmonella with both conventional culture methods and the kit and 89 were negative with both. One sample was negative by the culture method but positive by the kit assay. These results indicate that TaqMan is a reliable and rapid method for Salmonella analysis in the food industry. With this system, food samples can be analyzed for Salmonella in less than 20 h.