State-of-the-art speech recognition technologies for Russian language

Authors:
Daria Vazhenina;Irina Kipyatkova;Konstantin Markov;Alexey Karpov
Affiliations:
The University of Aizu, Japan;St.Petersburg Institute for Informatics and Automation of RAS (SPIIRAS), Russian Federation;The University of Aizu, Japan;St.Petersburg Institute for Informatics and Automation of RAS (SPIIRAS), Russian Federation
Venue:
Proceedings of the 2012 Joint International Conference on Human-Centered Computer Environments
Year:
2012

Citing 1
Cited 1

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HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics

Large vocabulary Russian speech recognition using syntactico-statistical language modeling

Speech Communication

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Abstract

In this paper, we present a review of the latest developments in the Russian speech recognition research. Although the underlying speech technology is mostly language-independent, differences between languages with respect to their structure and grammar have substantial effect on the recognition systems performance. The Russian language has a complicated word formation system, which is characterized by a high degree of inflection and unrigidness of the word order. This greatly reduces the predictive power of the conventional language models and consequently increases the error rate. Current statistical approach to speech recognition requires large amount of both speech and text data. There exist several Russian speech databases and their descriptions are given in this paper. In addition, we describe and compare several speech recognition systems developed in Russia as well as in some other countries. Finally we suggest some promising directions for further research in Russian speech technology.