A multimodal pattern recognition framework for speaker detection
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Recognizing the conversational context in which group interactions unfold has applications in machines that support collaborative work and perform automatic social inference using contextual knowledge. This paper addresses the task of discriminating one co ...
Within the HMM state mapping-based cross-lingual speaker adaptation framework, the minimum Kullback-Leibler divergence criterion has been typically employed to measure the similarity of two average voice state distributions from two respective languages fo ...
Within the HMM state mapping-based cross-lingual speaker adaptation framework, the minimum Kullback-Leibler divergence criterion has been typically employed to measure the similarity of two average voice state distributions from two respective languages fo ...
This paper investigates actual Venture Capital (VC) decision making as it occurs over time in its natural decision environment. Our qualitative analysis is based on a comprehensive, longitudinal data set comprising 11 years of archival data from a European ...
We present a fast method to detect humans from stationary surveillance videos. It is based on a cascade of LogitBoost classifiers which use covariance matrices as object descriptors. We have made several contributions. First, our method learns the correlat ...
State-of-the-art image and action classification systems often employ vocabulary-based representations. The classification accuracy achieved with such vocabulary-based representations depends significantly on the chosen histogram-distance. In particular, w ...
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The computational modeling of face-to-face interactions using nonverbal behavioral cues is an emerging and relevant problem in social computing. In the thesis, we have investigated individual social constructs in small groups such as dominance and status ( ...
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Context and activity recognition in complex scenarios is prone to data loss due to disconnections, sensor failure, transmission problems, etc. This generally implies significant changes in the recognition performance. In the case of classifier fusion fault ...
Spectral reflection prediction models, although effective, are impractical for certain industrial applications such as self-calibrating devices and online monitoring because of the requirements imposed by their calibration. The idea emerged to make the cal ...