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Emotion entrainment accounts for the rhythmic convergence of human emotions through social interactions. This phenomenon abounds in various disciplines, i.e. effervescency in soccer games, anger proliferation in violence incidents, or anxiety diffusion in disasters. Although emotion entrainment is highly relevant to the quality of human daily life, the principles underpinning this phenomenon is still...
California is the leading agricultural state in the United States. Agricultural production is being threatened by many factors: loss of agricultural land, water shortage, among others. In this paper, we employed an ordinary least square regression (OLS) model and a geographically weighted regression (GWR) model to examine the relationship between farming viability in California and three contributing...
In this paper, we propose an unsupervised phrase-based data selection model, address the problem of selecting no-domain-specific language model (LM) training data to build adapted LM for use. In spoken language translation (SLT) system, we aim at finding the LM training sentences which are similar to the translation task. Compared with the traditional bag-of-words models, the phrase-based data selection...
In this paper, we present a platform for aiding in the development and evaluation of novel ITS passive safety applications. Such applications work by having vehicles detect certain events that may be dangerous to other vehicles and disseminating reports about these events using wireless communication. A vehicle receiving the report about the event can then be warned. However, a large number of false...
This paper describes subspace constrained feature space maximum likelihood linear regression (FMLLR) for rapid adaptation. The test speaker's FMLLR rotation matrix is decomposed into the product of two triangular matrices which are restricted to lie in two subspaces spanned by upper and lower triangular matrix basis. The basis matrices could be obtained from training speaker's FMLLR matrices by maximum...
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