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N-grams in the speech of Czech and native speakers of English
Zvěřinová, Simona ; Gráf, Tomáš (advisor) ; Tichý, Ondřej (referee)
The diploma thesis is concerned with the analysis of recurrent word-combinations in the speech of advanced Czech speakers of English and native speakers of English. The data used for the analysis is extracted from two corpora, learner corpus LINDSEI and native speaker corpus LOCNEC. The aim of the thesis is to compare the two groups of speakers, determine differences in their use of recurrent word-combinations and compare the findings to previous studies involving speakers of different languages. The quantitative analysis is performed on a sample of 50 speakers from each corpus and the frequency data is used to compare the two groups as to the number of types of word-combinations they use and how frequently they do so. The qualitative analysis is performed on a sample of 15 speakers from each corpus to determine functional differences. Four categories of word-combinations are determined in the analysis. In the conclusion, the quantitative and qualitative findings are compared to previous research involving speakers of different languages. Keywords: spoken language, learner language, n-grams, n-gram analysis, recurrent word- combinations, lexical bundles, learner corpus
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Tagging a spoken learner corpus
Gillová, Lucie ; Gráf, Tomáš (advisor) ; Tichý, Ondřej (referee)
The aim of the thesis is to propose a tagging system for a learner corpus of spoken English which would, apart from tagging errors, focus also on the features specific for spoken language. Theoretical part, therefore, introduces basic concepts including learner language, the development of learner corpora in the last 20 years and both classical and computer-aided error analysis. Features typical of spoken language are described in the theoretical part as well since these are the focus of the research part of the thesis. The Louvain tagging system used for error-tagging of a leaner corpus of written language is used as the basis for the tagging system proposed in this thesis. Based on the analysis of 20 transcriptions taken from the Czech part of spoken learner corpus LINDSEI, modifications of the categories taken from the Louvain error-tagging system are proposed and new categories necessary for a better description of spoken language are introduced. The tagging system proposed in this thesis should make further analysis of the tagged corpus easier.
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N-grams in the speech of Czech and native speakers of English
Zvěřinová, Simona ; Gráf, Tomáš (advisor) ; Tichý, Ondřej (referee)
The diploma thesis is concerned with the analysis of recurrent word-combinations in the speech of advanced Czech speakers of English and native speakers of English. The data used for the analysis is extracted from two corpora, learner corpus LINDSEI and native speaker corpus LOCNEC. The aim of the thesis is to compare the two groups of speakers, determine differences in their use of recurrent word-combinations and compare the findings to previous studies involving speakers of different languages. The quantitative analysis is performed on a sample of 50 speakers from each corpus and the frequency data is used to compare the two groups as to the number of types of word-combinations they use and how frequently they do so. The qualitative analysis is performed on a sample of 15 speakers from each corpus to determine functional differences. Four categories of word-combinations are determined in the analysis. In the conclusion, the quantitative and qualitative findings are compared to previous research involving speakers of different languages. Keywords: spoken language, learner language, n-grams, n-gram analysis, recurrent word- combinations, lexical bundles, learner corpus
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Tagging a spoken learner corpus
Gillová, Lucie ; Gráf, Tomáš (advisor) ; Tichý, Ondřej (referee)
The aim of the thesis is to propose a tagging system for a learner corpus of spoken English which would, apart from tagging errors, focus also on the features specific for spoken language. Theoretical part, therefore, introduces basic concepts including learner language, the development of learner corpora in the last 20 years and both classical and computer-aided error analysis. Features typical of spoken language are described in the theoretical part as well since these are the focus of the research part of the thesis. The Louvain tagging system used for error-tagging of a leaner corpus of written language is used as the basis for the tagging system proposed in this thesis. Based on the analysis of 20 transcriptions taken from the Czech part of spoken learner corpus LINDSEI, modifications of the categories taken from the Louvain error-tagging system are proposed and new categories necessary for a better description of spoken language are introduced. The tagging system proposed in this thesis should make further analysis of the tagged corpus easier.
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