A distributed platform for speech recognition research
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Date
2016-06-17
Authors
Kozhirbayev, Zhanibek
Islam, Shynggys
Journal Title
Journal ISSN
Volume Title
Publisher
National Laboratory Astana
Abstract
Distributed and parallel processing of big data has been applied in various applications for the past few years. Moreover, huge advancements took place in usability, economic efficiency, and multiplicity of parallel processing systems, with big data analysis and speech recognition research supported by many researchers. In this paper we examined and investigated which parts of speech recognition research may be parallelized and computed using distributed computing platforms. Firstly, we address the case of efficiently computing n-gram statistics on MapReduce platforms to build a language model (LM). Secondly, we show how the Automated Speech Recognition (ASR) tool can work efficiently regarding the speed and fault-tolerance in distributed environment such as Sun GridEngine (SGE).
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Keywords
MapReduce, Hadoop ecosystem, Sun GridEngine, Distributed Computing