Abstract
The paper deals with extracting contexts for keywords found in text, in particular in Automatic Speech Recognition (ASR) output. We propose using a syntactic parser to find contexts by analysing the sentence structure, rather than simply using a window of several words on the left and right of the keyword, or the whole sentence. This method provides concise but meaningful contexts that are easily readable by humans and can also be used in applications such as thematic clustering. We describe the Russian SemSin system which combines a syntactic dependency parser and elements of semantic ontology. We demonstrate the use of SemSin for our task both for normal text and for recognition output, and outline the suggestions for future developments of our method.
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Acknowledgements
The work was financially supported by the Ministry of Education and Science of the Russian Federation, Contract 14.579.21.0008, ID RFMEFI57914X0008.
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Khomitsevich, O., Boyarsky, K., Kanevsky, E., Bulusheva, A., Mendelev, V. (2017). Flexible Context Extraction for Keywords in Russian Automatic Speech Recognition Results. In: Ignatov, D., et al. Analysis of Images, Social Networks and Texts. AIST 2016. Communications in Computer and Information Science, vol 661. Springer, Cham. https://doi.org/10.1007/978-3-319-52920-2_14
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DOI: https://doi.org/10.1007/978-3-319-52920-2_14
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