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An important aspect of Ambient Intelligence is a convenient user interface, supporting several user-friendly input modalities. Speech is one of the most natural modalities for man-machine interaction. Numerous applications in the context of Ambient Intelligence — whether referring to a single input modality or combining different ones — involve some pattern classification task. Experience shows that...
In this work, we present a model combination approach at the word level that aims to improve the modeling of spontaneous speech variabilities on a highly spontaneous, real life medical transcription task. The technique (1) separates speech variabilities into pre-defined classes, (2) generates speech variability specific acoustic and pronunciation models and (3) properly combines these models later...
Boosting algorithms have been successfully used to improve performance in a variety of classification tasks. Here, we suggest an approach to apply a popular boosting algorithm (called “AdaBoost.M2”) to Hidden Markov Model based speech recognizers, at the level of utterances. In a variety of recognition tasks we show that boosting significantly improves the best test error rates obtained with standard...
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