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This paper presents a new method on generating realistic human animation of various styles with given step constraints and a specific skeleton. Given a set of normal walking data captured from different subjects, a hierarchical geostatistical model is automatically learned to encode variety of walking styles by representing human body as a hierarchy of joint groups. For each child hierarchy level,...
Captured human motion data are used so that humanoid robots or computer graphics (CG) characters can behave naturally. Because the motion capture system is expensive, and time-consuming process is needed to acquire motion data, technology that enables to reuse existing motion data efficiently is required. This paper proposes motion retrieval method with natural language word based on stochastic correlation...
Tradition gait analysis systems capture the image of a walking subject from either front view or side view. Since the walking direction allowed by the systems is highly restricted, they are inconvenient for long-term evaluation in casual environments (such as home). This study proposes a human gait analysis system with much less restriction on walking direction. In the system, we use the images obtained...
It might be naïvely assumed that the performance of an Automatic Speech Recognition (ASR) system, and that of an Automatic Speech-to-Phoneme Alignment (ASPA) system using the same acoustic-phonetic models, would be closely related. However many researchers believe this relationship to be, at best weak - but this belief has not previously been tested in an objective and quantitative manner. This paper...
Goodness of pronunciation (GOP) is a confidence measure widely used in automatic pronunciation evaluation (APE) and it does not use the phone loop recognition lattice to calculate the confidence score. This paper presents a lattice-based GOP algorithm utilizing the information from the lattice, in order to obtain a more accurate confidence score. Experimental results reveal that the proposed LGOP...
Goodness of pronunciation (GOP) is a confidence measure widely used in automatic pronunciation evaluation (APE) and it does not use the phone loop recognition lattice to calculate the confidence score. This paper presents a lattice-based GOP algorithm utilizing the information from the lattice, in order to obtain a more accurate confidence score. Experimental results reveal that the proposed LGOP...
We outline how Human Activity Recognition systems based on Dynamic Bayesian Networks using a single camera may be adapted to be used in Visual Sensor Networks. It is assumed that current activity generates independent observations on some cameras in the network. Then, the activity is inferred by the accumulation of the evidences provided by the observations gathered. At the same time, some activities...
Posterior probability is mostly used for pronunciation evaluation. This paper introduces pronunciation space models to calculate posterior probability replacing traditional phone-based acoustic models, which makes the calculated posterior probability more precise. Pronunciation space models are constructed using unsupervised clustering method guided by human scores and phone-level posterior probability...
Automatic pronunciation evaluation (APE) can be implemented with a speech recognition model trained by standard, "golden" speakers. The pronunciation accuracy is then measured with the Goodness of Pronunciation (GOP) as reported in our earlier work [1]. In this paper, we investigate two main strategies for improving the evaluation: speaker adaptive training (SAT) for reducing the speaker-specific...
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