926 resultados para car security


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Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating non-critical in-car systems. Likelihood-maximising (LIMA) frameworks optimise speech enhancement algorithms based on recognised state sequences rather than traditional signal-level criteria such as maximising signal-to-noise ratio. Previously presented LIMA frameworks require calibration utterances to generate optimised enhancement parameters which are used for all subsequent utterances. Sub-optimal recognition performance occurs in noise conditions which are significantly different from that present during the calibration session - a serious problem in rapidly changing noise environments. We propose a dialog-based design which allows regular optimisation iterations in order to track the changing noise conditions. Experiments using Mel-filterbank spectral subtraction are performed to determine the optimisation requirements for vehicular environments and show that minimal optimisation assists real-time operation with improved speech recognition accuracy. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session.

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Acoustically, vehicles are extremely noisy environments and as a consequence audio-only in-car voice recognition systems perform very poorly. Seeing that the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem. However, implementing such an approach requires a system being able to accurately locate and track the driver’s face and facial features in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using this system, we present our results which show that using the Viola-Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose.

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In an automotive environment, the performance of a speech recognition system is affected by environmental noise if the speech signal is acquired directly from a microphone. Speech enhancement techniques are therefore necessary to improve the speech recognition performance. In this paper, a field-programmable gate array (FPGA) implementation of dual-microphone delay-and-sum beamforming (DASB) for speech enhancement is presented. As the first step towards a cost-effective solution, the implementation described in this paper uses a relatively high-end FPGA device to facilitate the verification of various design strategies and parameters. Experimental results show that the proposed design can produce output waveforms close to those generated by a theoretical (floating-point) model with modest usage of FPGA resources. Speech recognition experiments are also conducted on enhanced in-car speech waveforms produced by the FPGA in order to compare recognition performance with the floating-point representation running on a PC.

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Acoustically, car cabins are extremely noisy and as a consequence audio-only, in-car voice recognition systems perform poorly. As the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem by using audio visual automatic speech recognition (AVASR). However, implementing AVASR requires a system being able to accurately locate and track the drivers face and lip area in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using the AVICAR [1] in-car database, we show that the Viola- Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose for audio-visual speech recognition system.

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Whether by using electronic banking, by using credit cards, or by synchronising a mobile telephone via Bluetooth to an in-car system, humans are a critical part in many cryptographic protocols daily. We reduced the gap that exists between the theory and the reality of the security of these cryptographic protocols involving humans, by creating tools and techniques for proofs and implementations of human-followable security. After three human research studies, we present a model for capturing human recognition; we provide a tool for generating values called Computer-HUman Recognisable Nonces (CHURNs); and we provide a model for capturing human perceptible freshness.

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Globalization and liberalization, with the entry of many prominent foreign manufacturers, changed the automobile scenario in India, since early 1990‟s. Manufacturers such as Ford, General Motors, Honda, Toyota, Suzuki, Hyundai, Renault, Mitsubishi, Benz, BMW, Volkswagen and Nissan set up their manufacturing units in India in joint venture with their Indian counterpart companies, by making use of the Foreign Direct Investment policy of the Government of India, These manufacturers started capturing the hearts of Indian car customers with their choice of technological and innovative product features, with quality and reliability. With the multiplicity of choices available to the Indian passenger car buyers, it drastically changed the way the car purchase scenario in India and particularly in the State of Kerala. This transformed the automobile scene from a sellers‟ market to buyers‟ market. Car customers started developing their own personal preferences and purchasing patterns, which were hitherto unknown in the Indian automobile segment. The main purpose of this paper is to come up with the identification of possible parameters and a framework development, that influence the consumer purchase behaviour patterns of passenger car owners in the State of Kerala, so that further research could be done, based on the framework and the identified parameters

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By virtue of the volume and nature of their attributions, including secondary school as well as problem-areas such as security and traffic, the Brazilian states are the ultimate responsible entities for young people. This study argues in favour of granting greater freedom for the states to define their own public policy parameters to deal with local features and to increase the degree of learning about such actions at the national level. In empirical terms, the study assesses the impacts of new laws, such as the new traffic code (from the joint work with Leandro Kume, EPGE/FGV doctor’s degree student) and traces the statistics for specific questions like drugs, violence and car accidents. The findings show that these questions produce different results for young men and women.The main characters in these dramas are young single males, suggesting the need for more distinguished public policies according not only to age, but also by gender. The study also reveals that the magnitude of these problems changes according to the youth’s social class. Prisons concern poorer men (except for the functional illiterate) while fatal car accidents and the confessed use of drugs concern upper-class boys.

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Includes bibliography

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Includes bibliography