Arkadiusz Nagórski

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This paper presents a method designed to select a limited set of maximally information rich speech data from a database for optimal training and diagnostic testing of Automatic Speech Recognition (ASR) systems. The method uses Principal Component Analysis (PCA) to map the variance of the speech material in a database into a low-dimensional space, followed(More)
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