Titlebook: In-Vehicle Corpus and Signal Processing for Driver Behavior; Kazuya Takeda,John H. L. Hansen,Hüseyin Abut Book 2009 Springer-Verlag US 200

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A New Method for Evaluating Mental Work Load In ,-Back Tasks,ver, there does not exist any quantitative method for evaluating mental work load in real time. This motivates the study of proposing a new method to evaluate the influence of mental work load caused by information processing demand. Our method focuses on involuntary eye movement of human, which is

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Estimation of Acoustic Microphone Vocal Tract Parameters from Throat Microphone Recordings,rd the acoustic sounds in the form of vibrations from skin-attached sensors, they are more robust and highly correlated with the acoustic speech signal. We investigate the correlation of throat and acoustic microphone recordings. We propose a hidden Markov model (HMM)-based structure to build a mapp

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Cross-Probability Model Based on Gmm for Feature Vector Normalization, earlier and it was proved to be effective to compensate environment mismatch. MEMLIN is an empirical feature vector normalization technique which models clean and noisy spaces with Gaussian mixture models, GMMs; and the probability of the clean model Gaussian, given the noisy model one and the nois

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Prediction of Driving Actions from Driving Signals,lems. One of these problems is distraction whereby machine operation and voice conversations influence the driver. Even the use of a simple speech interface may affect the driving operation. We consider that a spoken dialogue system which can understand the driver‘s situation and change its dialogue

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,Design of Audio-Visual Interface for Aiding Driver’s Voice Commands in Automotive Environment,ition under adverse automobile noisy environment. In particular, we employ lip-reading as an added feature for enhanced speech recognition. Lip motion feature is extracted by active shape models and the corresponding hidden Markov models are constructed for lip-reading. For realizing efficient hidde

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