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We have previously proposed unsupervised cross-validation (CV) adaptation that introduces CV into an iterative unsupervised batch mode adaptation framework to suppress the influence of errors in an internally generated recognition hypothesis and have shown that it improves recognition performance. However, a limitation was that the experiments were performed using only a clean speech recognition task...
We propose unsupervised cross-validation (CV) and aggregated (Ag) adaptation algorithms that integrate the ideas of ensemble methods, such as CV and bagging, in the iterative unsupervised batch-mode adaptation framework. These algorithms are used to reduce overtraining problems and to improve speech recognition performance. The algorithms are constructed on top of a general parameter estimation technique...
This paper presents the design and implementation of 3D Auditory Scene Visualizer based on the visual information seeking mantra, ``overview first, zoom and filter, then details on demand''. The machine audition system called HARK captures 3D sounds with a microphone array.The natural language processing called SalienceGraph visualizes topic transition by using discourse salience. The 3D visualizer...
If machine audition can recognize an auditory scene containing simultaneous and moving talkers, what kinds of awareness will people gain from an auditory scene visualizer? This paper presents the design and implementation of 3D Auditory Scene Visualizer based on the visual information seeking mantra, i.e., ldquooverview first, zoom and filter, then details on demandrdquo. The machine audition system...
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