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This paper presents a robust automatic speech recognition (ASR) system as multimedia interface for car navigation. In front-end, we use the minimum-mean square error (MMSE) enhancement to suppress the background in-car noise and then compensate the spectrum components distorted by noise over-reduction by smoothing technologies. In acoustic model training, an immunity learning scheme is adopted, in which pre-recorded car noises are artificially added to clean training utterances to imitate the in-car environment. The immunity scheme makes the system robust to both residual noise and speech enhancement distortion. In the context of Mandarin speech recognition, a special issue is the diversification of Chinese dialects, i.e. the pronunciation difference among accents decreases the recognition performance if the acoustic models are trained with an unmatched accented database. We propose to train the models with multiple accented Mandarin databases to solve this problem. The efficiency of the proposed ASR system is confirmed in evaluations. Keywords: Speech Recognition, Accented Mandarin, In-Car Noise, Speech Enhancement, Immunity Learning. [ABSTRACT FROM AUTHOR]

An analytical performance model for out of order issue superscalar micro-processors is presented. This model quantifies the performance impacts of micro-architecture design options including memory hierarchy, branch prediction, issue width and changes in pipeline depth at all pipeline stages. The model requires a minimal number of cycle accurate and trace driven simulations to calibrate and once calibrated estimates performance by formula. The model estimates the performance of arbitrary micro-architecture configurations with an average error of 6.4%. During early design stages when cycle accurate simulation is prohibitive an analytical model can provide guidance to designers to increase design quality and reduce design effort. This allows the design of an embedded processor to be rapidly tuned to its application by reducing the cost of exploring the design space. [ABSTRACT FROM AUTHOR]

The contribution presents an integrated system for automatic acquisition of a human torso model, using different input images. The output model consists of two free-form surface patches (with texture maps) for the torso and the arms. Also, the positions for the neck joint on the torso, and six joint positions on the arms (for the wrist, elbow and shoulder) are determined automatically. We present reconstruction results, and, as application, a simple tracking system for arm movements. [ABSTRACT FROM AUTHOR]

A morphological edge detector for robust real time image segmentation is proposed in this paper. Different from traditional thresholding methods that determine the threshold based on image gray level distribution, our method derives the threshold from object boundary point gray values and the boundary points are detected in the image using the proposed morphological edge detector. Firstly, the morphological edge detector is applied to compute the image morphological gradients. Then from the resultant image morphological gradient histogram, the object boundary points can be selected, which have higher gradient values than those of points within the object and background. The threshold is finally determined from the object boundary point gray values. Thus noise points inside the object and background are avoided in threshold computation. Experimental results on currency image segmentation for real time printing quality inspection are rather encouraging. [ABSTRACT FROM AUTHOR]

As the genome research continues to grow and genomic information avalanches at the speed of light, biological research labs are facing continuous effort to redefine the scale and scope of their research. Large-scale research applications such as high-throughput sequencing and cDNA microarrays are becoming standard tools in most labs, demanding an increasing ability to generate and handle a large amount of highly purified DNA templates (1). As a result, developing protocols that address the rising needs in sample tracking, robotic compatibility, and efficient integration has become a priority. [ABSTRACT FROM AUTHOR]