In this paper we present an overview of state-of-the-art approaches for speaker identification. Due to the increased number of dialogue system applications the interest in that field has grown significantly in recent years. Nevertheless, there are many open issues in the field of automatic speaker identification. Among them the choice of the appropriate speech signal features and machine learning algorithms could be mentioned. We make here an overview of modern methods designed for the problem of speaker identification. We also describe here our direction for possible improvements to the automated speaker identification.

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In this paper we present an overview of the stateof-the-art approaches for speech recognition of the Russian language. Since Russian is a highly inflective language with a complex mechanism of word formation, the main approaches for English speech recognition are not optimally applicable for Russian speech, at least directly and without appropriate adaptation. We make here an overview of some modern methods designed specially for Russian and other languages with similar word formation mechanism and grammar basis. Among them there are morpheme based speech recognition and compound language modeling. We also describe here our direction for possible subsequent Russian speech recognizer improvements.

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