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The continuous monitoring and recording of food intake amount without user intervention is very useful in the prevention of obesity and metabolic diseases. I adopted a technique that automatically recognizes food intake amount by combining the identification of food types through image recognition and a technique that uses acoustic modality to recognize chewing events. The accuracy of using audio signal to detect eating activity is seriously degraded in a noisy environment. To alleviate this problem, contact sensing methods have conventionally been adopted, wherein sensors are attached to the face or neck region to reduce external noise. Such sensing methods, however, cause dermatological discomfort and a feeling of cosmetic unnaturalness for most users. In this study, a noise-robust and non-contact sensing method was employed, wherein ultrasonic Doppler shifts were used to detect chewing events. The experimental results showed that the mean absolute percentage errors (MAPEs) of an ultrasonic-based method were comparable with those of the audio-based method (15.3 vs. 14.6) when 30 food items were used for experiments. The food intake amounts were estimated for eight subjects in several noisy environments (cafeterias, restaurants, and home dining rooms). For all subjects, the estimation accuracy of the ultrasonic method was not degraded (the average MAPE was 15.02) even under noisy conditions. These results show that the proposed method has the potential to replace the manual logging method.

The quality of speech reproduced using conventional single-channel speech enhancement schemes is seriously affected by acoustic noise level. Nonacoustic sensors have the ability to reveal certain speech attributes that are lost in noisy acoustic signals. This study validated the use of ultrasonic doppler frequency shifts caused by facial movements for enhancing audio speech contaminated by high levels of acoustic noise. A 40 kHz ultrasonic beam is incident to a speaker’s face. The received signals were first demodulated and converted to a spectral feature parameter. The spectral feature derived from the ultrasonic Doppler signal (UDS) was concatenated with spectral features from noisy speech, which were then used to estimate the magnitude of the spectrum of clean speech. A nonlinear regression approach was employed in this estimation where the relationship between audio-UDS features and the corresponding clean speech is represented by deep neural networks (DNN). The feasibility of the proposed enhancement method was tested on a 1 h audio-UDS corpus and four different types of noise data. The results showed that, both objectively and subjectively, the best performance was obtained when the audio and UDS were used cooperatively. A correlation analysis was also carried out to investigate the usefulness of multi-directional ultrasonic sensing. The results showed that the performance was affected by the number of the adopted UDS channels, particularly in cases of low levels of SNRs.

Reliable, user-friendly and convenient sensing is highly desirable when the continuous monitoring of food intake is necessary. In this paper, food intake monitoring was during the processes of chewing and swallowing. Acoustic Doppler sonar (ADS) detected chewing and swallowing events that were non-contact and free from acoustic interference. When a 40 kHz ultrasonic beam was focused on the lower jaw and neck, movements of the chin and neck cause Doppler frequency shifts and an amplitude envelope modulation of ultrasonic signals. Hence, it was possible to detect chewing and swallowing events using Doppler frequency shifts in the received ultrasound signals. To prevent suspicious chew events caused by talking from being recognized as food intake events, the log-filter bank energy of the voice band was also taken into consideration. Automatic detection of chewing and swallowing events was achieved via an artificial neural network. The experimental results showed that the proposed ADS-based food intake detection method yielded promising results with maximum recognition rates of 91.4% and 78.4% for chewing and swallowing, respectively. As a result, it was confirmed that the proposed food intake detection method using ultrasonic Doppler yielded high rates of recognition without discomfort to the user from continuous skin contact.

A large amount of parallel training corpus is necessary for robust, high-quality voice conversion. However, such parallel data may not always be available. This letter presents a new voice conversion method that needs no parallel speech corpus, and adopts a restricted Boltzmann machine (RBM) to represent the distribution of the spectral features derived from a target speaker. A linear transformation was employed to convert the spectral and delta features. A conversion function was obtained by maximizing the conditional probability density function with respect to the target RBM. A feasibility test was carried out on the OGI VOICES corpus. Results from the subjective listening tests and the objective results both showed that the proposed method outperforms the conventional GMM-based method.

Spin-orbit torques arising from the spin-orbit coupling of non-magnetic heavy metals allow electrical switching of perpendicular magnetization. However, the switching is not purely electrical in laterally homogeneous structures. An extra in-plane magnetic field is indeed required to achieve deterministic switching, and this is detrimental for device applications. On the other hand, if antiferromagnets can generate spin-orbit torques, they may enable all-electrical deterministic switching because the desired magnetic field may be replaced by their exchange bias. Here we report sizeable spin-orbit torques in IrMn/CoFeB/MgO structures. The antiferromagnetic IrMn layer also supplies an in-plane exchange bias field, which enables all-electrical deterministic switching of perpendicular magnetization without any assistance from an external magnetic field. Together with sizeable spin-orbit torques, these features make antiferromagnets a promising candidate for future spintronic devices. We also show that the signs of the spin-orbit torques in various IrMn-based structures cannot be explained by existing theories and thus significant theoretical progress is required.

A voice transformation (VT) method that can make the utterance of a source speaker mimic that of a target speaker is described. Speaker individuality transformation is achieved by altering four feature parameters, which include the linear prediction coefficients cepstrum (LPCC), Δ LPCC, LP-residual and pitch period. The main objective of this study involves construction of an optimal sequence of features selected from a target speaker’s database, to maximize both the correlation probabilities between the transformed and the source features and the likelihood of the transformed features with respect to the target model. A set of two-pass conversion rules is proposed, where the feature parameters are first selected from a database then the optimal sequence of the feature parameters is then constructed in the second pass. The conversion rules were developed using a statistical approach that employed a maximum likelihood criterion. In constructing an optimal sequence of the features, a hidden Markov model (HMM) with global control variables (GCV) was employed to find the most likely combination of the features with respect to the target speaker’s model. The effectiveness of the proposed transformation method was evaluated using objective tests and formal listening tests. We confirmed that the proposed method leads to perceptually more preferred results, compared with the conventional methods.

The present study tested a new stereo playback system that effectively cancels cross-talk signals at an arbitrary listening position. Such a playback system was implemented by integrating listener position tracking techniques and crosstalk cancellation techniques. The entire listening space was partitioned into a number of non-overlapped cells and a crosstalk cancellation filter was assigned to each cell. The listening space partitions and the corresponding crosstalk cancellation filters were constructed by maximizing the average channel separation ratio (CSR). Since the proposed method employed cell-based crosstalk cancellation, estimation of the exact position of the listener was not necessary. Instead, it was only necessary to determine the cell in which the listener was located. This was achieved by simply employing an artificial neural network (ANN) where the time delay to each pair of microphones was used as the ANN input and the ANN output corresponded to the index of cells. The experimental results showed that more than 95% of the experimental listening space had a CSR ≥ 10 dB when the number of clusters exceeded 12. Under these conditions, the correlation between the true directions of the virtual sound sources and the directions recognized by the subjects was greater than 0.9.

In the present study, a new stereophonic playback system was proposed, where the cross-talk signals would be reasonably cancelled at an arbitrary listener position. The system was composed of two major parts: the listener position tracking part and the sound rendering part. The position of the listener was estimated using acoustic signals from the listener (i.e. voice or hand-clapping signals). A direction of arrival (DOA) algorithm was adopted to estimate the directions of acoustic sources where the room reverberation effects were taken into consideration. A Crosstalk cancellation filter was designed using a free-field model. To determine the maximum tolerable shift of the listener position, a quantitative analysis of the channel separation ratio according to the displacement of the listener position was performed. Prototype hardware was implemented using a microprocessor board, a DSP board, a multi-channel ADC board and an analog frontend. The results showed that the average mean square error between the true direction of a listener and the estimated direction was about 5 degrees. More than 80% of the tested subjects indicated that better stereo images were obtained by the proposed system, compared with the non-processed signals.

Myoelectric signals (MESs) from the speaker's mouth region have been successfully shown to improve the noise robustness of automatic speech recognizers (ASRs), thus promising to extend their usability in implementing noise-robust ASR. In the recognition system presented herein, extracted audio and facial MES features were integrated by a decision fusion method, where the likelihood score of the audio-MES observation vector was given by a linear combination of class-conditional observation log-likelihoods of two classifiers, using appropriate weights. We developed a weighting process adaptive to SNRs. The main objective of the paper involves determining the optimal SNR classification boundaries and constructing a set of optimum stream weights for each SNR class. These two parameters were determined by a method based on a maximum mutual information criterion. Acoustic and facial MES data were collected from five subjects, using a 60-word vocabulary. Four types of acoustic noise including babble, car, aircraft, and white noise were acoustically added to clean speech signals with SNR ranging from -14 to 31 dB. The classification accuracy of the audio ASR was as low as 25.5%. Whereas, the classification accuracy of the MES ASR was 85.2%. The classification accuracy could be further improved by employing the proposed audio-MES weighting method, which was as high as 89.4% in the case of babble noise. A similar result was also found for the other types of noise.

A voice transformation method which changes the source speaker's utterances so as to sound similar to those of a target speaker is described. Speaker individuality transformation is achieved by altering the LPC cepstrum, average pitch period and average speaking rate. The main objective of the work involves building a nonlinear relationship between the parameters for the acoustical features of two speakers, based on a probabilistic model. The conversion rules involve the probabilistic classification and a cross correlation probability between the acoustic features of the two speakers. The parameters of the conversion rules are estimated by estimating the maximum likelihood of the training data. To obtain transformed speech signals which are perceptually closer to the target speaker's voice, prosody modification is also involved. Prosody modification is achieved by scaling excitation spectrum and time scale modification with appropriate modification factors. An evaluation by objective tests and informal listening tests clearly indicated the effectiveness of the proposed transformation method. We also confirmed that the proposed method leads to smoothly evolving spectral contours over time, which, from a perceptual standpoint, produced results that were superior to conventional vector quantization (VQ)-based methods

The composite metal hydride MgH 2 –Me x O y powder was synthesized by high energy ball milling (Me x O y = V 2 O 5 , Cr 2 O 3 , Al 2 O 3 , Fe 2 O 3 ). The hydrogen absorption kinetics of composite metal hydride was determined by automated PCT measurements. The poor kinetics of MgH 2 were greatly improved with an addition of oxide. In absorption, the catalytic effects of Al 2 O 3 and Cr 2 O 3 were remarkable at 300 °C with hydrogen capacity up to 4.09 and 4.02 wt%. At 250 and 200 °C, V 2 O 5 showed that the fastest kinetics and hydrogen absorption capacities up to 3.2 and 2.25 wt%.

The automatic labeling of a large speech corpus plays an important role in the development of a high-quality Text-To-Speech (TTS) synthesis system. This paper describes a method for the automatic labeling of speech signals, which mainly involves the construction of a large database for a TTS synthesis system. The main objective of the work involves the refinement of an initial estimation of phone boundaries which are provided by an alignment, based on a Hidden Markov Model. A multilayer perceptron (MLP) was employed to refine the phone boundaries. To increase the accuracy of phoneme segmentation, several specialized MLPs were individually trained based on phonetic transition. The optimum partitioning of the entire phonetic transition space and the corresponding MLPs were constructed from the standpoint of minimizing the overall deviation from the hand-labeling position. The experimental results showed that more than 93% of all phone boundaries have a boundary deviation from a reference position smaller than 20 ms. We also confirmed that the database constructed using the proposed method produced results that were perceptually comparable to a hand-labeled database, based on subjective listening tests.

Boron carbide thin coatings were deposited on silicon wafers by DC magnetron sputtering using a B 4 C target with Ar as processing gas. Various amounts of methane gas (CH 4 ) were added in the deposition process to better understand their influence on tribological properties of the coatings. Reciprocating wear tests employing an oscillating friction wear tester were performed to investigate the tribological behaviors of the coatings in ambient environment. The chemical characteristics of the coatings and worn surfaces were studied using X-ray photoelectron spectroscopy (XPS) and Auger electron spectroscopy (AES). It revealed that CH 4 addition to Ar processing gas strongly affected the tribological properties of sputtered boron carbide coating. The coefficient of friction was reduced approximately from 0.4 to 0.1, and wear resistance was considerably improved by increasing the ratio of CH 4 gas component from 0 to 1.2 vol.%. By adding an optimal amount of CH 4 (∼1.2 vol.%) in the deposition process the boron carbide coating exhibited the lowest friction and highest wear resistance.

A new antibacterial agent gemifloxacin was labelled with carbon-14 for studies of pharmacokinetics and metabolism, the label was located in position 3 of the quinolone ring system. The overall radiochemical yield of the 14-step synthesis, starting from [2-14C]sodium acetate was 16.6%, and the radiochemical purity 97.5%. Copyright © 2004 John Wiley & Sons, Ltd.

The 6061 (Al–1.01 wt% Mg–1.07 wt% Si) Al alloy was fabricated by powder metallurgy, and then subjected to equal channel angular pressing. The microstructure and mechanical properties such as microhardness and tensile properties of the equal channel angular pressed P/M 6061 Al alloy were investigated. The P/M 6061 Al alloy had an initial grain size of approximately 20 μm. After two pressings at 373 K using route A, the sample revealed microstructure of subgrain bands with a length of ∼0.8 μm and a width of ∼0.3 μm. The subgrain bands became larger above 1 μm in length and width after two pressings at 573 K. An equiaxed ultra-fine grained structure with the mean grain size of ∼0.5 μm was obtained after four repetitive equal channel angular pressings at 473 K using route A and C. The microhardness of P/M 6061 Al alloys was drastically increased from about 40 to 80 Hv by two repetitive pressings at 373 K. However, the microhardness decreased with increasing the pressing temperature. The tensile strength of 6061Al alloy before the equal channel angular pressing was 95 MPa, whereas it increased to both 248 MPa after two pressings at 373 K and 130 MPa after four pressings at 473 K, which was superior to that of a commercial 6061-O Al alloy.

In text-to-speech synthesis, spectral smoothing is often employed to reduce artifacts at unit-joining points. A context-adaptive smoothing method is proposed in this letter, where the amount of smoothing is determined according to context information. Discontinuities at unit boundaries are predicted by a regression tree, and smoothing factors are computed by using predicted discontinuities and real discontinuities at unit boundaries. Experimental results are presented to demonstrate the effectiveness of the proposed method.

Current induced spin-orbit effective magnetic fields in metal/ferromagnet/oxide trilayers provide a new way to manipulate the magnetization, which is an alternative to the conventional current induced spin transfer torque arising from noncollinear magnetization. Ta/CoFeB/MgO structures are expected to be useful for non-volatile memories and logic devices due to its perpendicular anisotropy and large current induced spin-orbit effective fields. However many aspects such as the angular and temperature dependent phenomena of the effective fields are little understood. Here, we evaluate the angular and temperature dependence of the current-induced spin-orbit effective fields considering contributions from both the anomalous and planar Hall effects. The longitudinal and transverse components of effective fields are found to have strong angular dependence on the magnetization direction at 300 K. The transverse field decreases significantly with decreasing temperature, whereas the longitudinal field shows weaker temperature dependence. Our results reveal important features and provide an opportunity for a more comprehensive understanding of current induced spin-orbit effective fields.

The microstructure of ultrafine grained low carbon steel processed with repetitive equal channel angular pressing was investigated. A submicron ferrite grain size of ∼0.2 μm was achieved by pressings of up to 12 passes. Microstructural examination by TEM with SAD pattern on the pressed samples revealed the presence of high density dislocations inside the ferrite grains and ill-defined grain boundaries. These features became more significant as the number of pressings increased. The static annealing of the pressed samples at 753 K up to 24 hrs resulted in a recovery which was associated with the absorption of the dislocations by the grain boundaries. However, the recovery was inhibited as the number of pressings increased. The annealing process also led to the precipitation of cementite particles in ferrite colonies. The presence of precipitated particles inside the ferrite grains enhanced the microstructural stability of the low carbon steel at elevated temperatures.

Previous studies have shown that a concatenative speech synthesis system with a large database produces more natural sounding speech. We apply this paradigm to the design of improved very low bit rate speech coders (sub 1000 b/s). The proposed speech coder consists of unit selection, prosody coding, prosody modification and waveform concatenation. The encoder selects the best unit sequence from a large database and compresses the prosody information. The transmitted parameters include unit indices and the prosody information. To increase naturalness as well as intelligibility, two costs are considered in the unit selection process: an acoustic target cost and a concatenation cost. A rate-distortion-based piecewise linear approximation is proposed to compress the pitch contour. The decoder concatenates the set of units, and then synthesizes the resultant sequence of speech frames using the harmonic+noise model (HNM) scheme. Before concatenating units, prosody modification which includes pitch shifting and gain modification is applied to match those of the input speech. With single speaker stimuli, a comparison category rating (CCR) test shows that the performance of the proposed coder is close to that of the 2400-b/s MELP coder at an average bit rate of about 800-b/s during talk spurts.

The synthesis of 14 C-2-amino-9-(3-hydroxymethyl-4-isopropoxycarbonyloxybut-1-yl)purine from [1- 14 C] diethyl malonate is described. The overall radiochemical yield of the product in a nine-step sequence was 16.1%, and the compound's radiochemical purity was 98.5%

This letter addresses a temporal decomposition (TD) technique that is based on a rate-distortion criterion. In the proposed TD scheme, a set of interpolation functions is constructed from a given training corpus, and the optimum target points are found in the sense of minimizing, not only spectral distortion, but also bit rates. The results of the simulation show that an average spectral distortion of about 1.4 dB can be achieved at an average bit rate of about 8 bits/frame.

It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model.

We theoretically investigate the threshold current for thermally activated switching of a perpendicular magnet by spin-orbit spin torque. Based on the Fokker-Planck equation, we obtain an analytic expression of the switching current, in agreement with numerical result. We find that thermal energy barrier exhibits a quasi-linear dependence on the current, resulting in an almost linear dependence of switching current on the log-scaled current pulse-width even below 10 ns. This is in stark contrast to standard spin torque switching, where thermal energy barrier has a quadratic dependence on the current and the switching current rapidly increases at short pulses. Our results will serve as a guideline to design and interpret switching experiments based on spin-orbit spin torque, 18 pages, 4 figures

We theoretically investigate the switching of a perpendicular magnetic layer by in-plane charge current due to the spin Hall effect. We find that, in the high damping regime, the threshold switching current is independent of the damping constant, and is almost linearly proportional to both effective perpendicular magnetic anisotropy field and external in-plane field applied along the current direction. We obtain an analytic expression of the threshold current, in excellent agreement with numerical results. This expression can be used to determine the physical quantities associated with spin Hall effect, and to design relevant magnetic devices based on the switching of perpendicular magnetic layers., Comment: 16 pages, 3 figures