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ANALYSIS OF DATA BALANCING PROBLEM IN ACOUSTIC MODELING OF AUTOMATIC SPEECH RECOGNITION SYSTEM

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The problem of data balancing for training of acoustic models for automatic speech recognition system is considered. A metric is proposed which enables an explicit account for the data level in a cluster during triphone clustering. The proposed approach is shown to improve the quality of speech recognition.

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