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Among the technological developments pushed by the adoption of Through Silicon Vias and 3D Stacked IC technologies, wafer thinning on a temporary carrier has become a critical element in device processing over the past years. First generation of adhesive materials enabled the integration of the first devices at the expense of capping the thermal budget. Hence new generation materials are being explored...
Operation of 1.3-µm uncooled 28-Gbps EA/DFB lasers at the lowest-so-far-reported voltage was demonstrated. To achieve high-quality waveforms, the MQW structure was optimized, and a novel EA operation condition was proposed. Consequently, the lasers achieved high-quality eye openings with modulation amplitude of 1.0 Vpp from 25 °C to 85 °C.
This paper presents UX Gymnastics, a collaborative activity for learning user experience (UX) theory and concepts through full body representation. UX Gymnastics participants are tasked to twist and contort their bodies to represent UX theory and concepts presented by the activity facilitator. The activity may involve complex physical movements and exercise. By adopting full body collaborative activities,...
We propose a novel diagnostic technique for identifying loss factors using 1-µm-band mode-detection OTDR. The loss ratio between the LP01 and LP11 modes of backscattered light determines the macrobending or fusion splicing state.
Among the technological developments pushed by the emergence of 3D-ICs, wafer thinning has become a key element in device processing over the past years. As technology matures, more emphasis is now being put on the overall cost of ownership, which is still regarded as a refraining element for technology adoption. Therefore novel temporary bond concepts and materials are being explored to further bring...
The explosive growth of computer networking enormously increases security costs in universities. It is necessary to encourage the cooperation of students, faculty, and staff through education and training of information ethics, together with improving management and technologies, and as a consequence, to reduce university costs. We have been producing collections of video clips for information ethics...
Corpus-based speech enhancement has received increasing attention recently since it shows high enhancement performance in highly non-stationary noisy environments by precisely modeling the long-term temporal dynamics of speech. However, it has a disadvantage in that the cost is very high for searching the longest matching clean speech segments from a multi-condition parallel speech corpus. This paper...
This paper proposes an efficient one-pass decoding method for realtime speech recognition employing a recurrent neural network language model (RNNLM). An RNNLM is an effective language model that yields a large gain in recognition accuracy when it is combined with a standard n-gram model. However, since every word probability distribution based on an RNNLM is dependent on the entire history from the...
This paper presents fast zero-resource spoken term detection (STD) in a large-scale data set, by using a hierarchical graph-based similarity search method (HGSS). HGSS is an improved graph-based similarity search method (GSS) in terms of a search space for high-speed performance. Instead of a degree-reduced k-nearest neighbor (k-DR) graph for GSS, a hierarchical k-DR graph, which is constructed based...
Substrate noise coupling from digital circuits causes degradation of performance of analog circuits on the same LSI chip. Generally large area on the chip is necessary to reduce the substrate coupling. In this paper, a proposed method eliminates the substrate coupling by extension of the impedance balance control technique which was proposed by the authors. The impedance balance condition on the LSI...
A novel sampling method is proposed for estimating a continuous multi-scale mixture model. The multi-scale mixture models we assume have a hierarchical structure in which each component of the mixture is represented by a Gaussian mixture model (GMM). In speaker modeling from speech, this GMM represents intra-speaker dynamics derived from the difference in the attributes such as phoneme contexts and...
A biometric authentication method is proposed based on hyper spectral image data derived from the palm of the hand. The data are acquired using a recently developed device that captures reflectance across the 396.37-990.64 nm range with a spectral resolution of 0.93 nm. The acquired image data represent the distributions of various biological substances. First, the proposed method computes the spatial...
This paper presents a neighborhood graph index approach for query-by-example search using dynamic time warping (DTW) on Gaussian mixture model (GMM) posteriorgram sequences. The approach is intended to achieve a significant speed-up of a spoken term detection (STD) task for resource-limited situations. The proposed method employs a degree-reduced k-nearest neighbor (k-DR) graph as an index. A set...
Techniques for estimating recognition rates without using reference transcriptions are essential if we are to judge whether or not speech recognition technology is applicable to a new task. We have proposed a discriminative recognition rate estimation (DRRE) method for 1-best recognition hypotheses and shown its good estimation performance experimentally. In this paper, we extend our DRRE to N-best...
Recently, structured classification approaches have been considered important with a view to achieving unified modeling of the acoustic and linguistic aspects of speech recognizers. With these approaches, unified representation is achieved by directly optimizing a score function that measures the correspondence between the input and output of the system. Since structured classifiers typically employ...
In this paper, we propose a tuning-free Bayesian linear regression approach for speaker adaptation. We first formulate feature space variational Bayesian linear regression (fVBLR). Using a lower bound as the objective function, we can optimize a binary tree structure and control parameters for prior density scaling. We experimentally verified the proposed fVBLR could achieve performance comparable...
This paper proposes a new approach for unsupervised model adaptation using a discriminative criterion. Discriminative criteria for acoustic model training have been widely used and have provided significantly improved performance compared with models trained usingmaximumlikelihood. However, discriminative criteria are sensitive to errors in reference transcriptions, which limits their applicability...
Techniques for estimating recognition rates without using reference transcriptions are essential if we are to judge whether or not speech recognition technology is applicable to a new task. This paper proposes two recognition rate estimation methods for continuous speech recognition. The first is an easy-to-use method based on a word alignment network (WAN) obtained from a word confusion network through...
The spread spectrum clock (SSC) is known to have the ability to reduce the quasi-peak level of clock harmonics noise. However, SSC may also have an adverse effect on wireless systems. In the present paper, a SSC with optimized parameters is developed that has a beneficial effect on one-segment broadcasting, which is based on orthogonal frequency division multiplexing and is used for mobile TV in some...
The discriminative optimization of decoding networks is important for minimizing speech recognition error. Recently, several methods have been reported that optimize decoding networks by extending weighted finite state transducer (WFST)-based decoding processes to a linear classification process. In this paper, we model decoding processes by using conditional random fields (CRFs). Since the maximum...
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