Abstract
Abstract. This paper deals with the clustering task for Russian texts obtained using automatic speech recognition (ASR). The input for processing are recognition result for phone call recordings and manual text transcripts for these calls. We present a comparative analysis of clustering results for recognition texts and manual text transcripts, make an evaluation of how recognition quality affects clustering and explore approaches to increasing clustering quality by using stop words and Latent Semantic Indexing (LSI).
This work was partially financially supported by the Government of Russian Federation, Grant 074-U01.
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Popova, S., Khodyrev, I., Ponomareva, I., Krivosheeva, T. (2014). Automatic Speech Recognition Texts Clustering. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2014. Lecture Notes in Computer Science(), vol 8655. Springer, Cham. https://doi.org/10.1007/978-3-319-10816-2_59
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DOI: https://doi.org/10.1007/978-3-319-10816-2_59
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