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Description
  • Automatic detection of misannotated words in single-speaker read-speech corpora is investigated in this paper. Support vector machine (SVM) classifier was proposed to detect the misannotated words. Its performance was evaluated with respect to various word-level feature sets. The SVM classifier was shown to perform very well with both high precision and recall scores and with F1 measure being almost 88%. This is a statistically significant improvement over a traditionally used outlier-based detection method.
  • Automatic detection of misannotated words in single-speaker read-speech corpora is investigated in this paper. Support vector machine (SVM) classifier was proposed to detect the misannotated words. Its performance was evaluated with respect to various word-level feature sets. The SVM classifier was shown to perform very well with both high precision and recall scores and with F1 measure being almost 88%. This is a statistically significant improvement over a traditionally used outlier-based detection method. (en)
Title
  • SVM-Based Detection of Misannotated Words in Read Speech Corpora
  • SVM-Based Detection of Misannotated Words in Read Speech Corpora (en)
skos:prefLabel
  • SVM-Based Detection of Misannotated Words in Read Speech Corpora
  • SVM-Based Detection of Misannotated Words in Read Speech Corpora (en)
skos:notation
  • RIV/49777513:23520/13:43919403!RIV14-TA0-23520___
http://linked.open...avai/predkladatel
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  • P(TA01030476)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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  • 109272
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  • RIV/49777513:23520/13:43919403
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  • read speech corpora; support vector machine; classification; annotation error detection (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [EC71A57E7427]
http://linked.open...v/mistoKonaniAkce
  • Plzeň
http://linked.open...i/riv/mistoVydani
  • Heidelberg
http://linked.open...i/riv/nazevZdroje
  • Text, Speech, and Dialogue 16th International Conference, TSD 2013, Pilsen, Czech Republic, September 1-5, 2013. Proceedings
http://linked.open...in/vavai/riv/obor
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  • Matoušek, Jindřich
  • Tihelka, Daniel
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
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  • 10.1007/978-3-642-40585-3_58
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  • Springer-Verlag
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  • 978-3-642-40584-6
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  • 23520
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