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Pragmatic Markers in Dialogue and Monologue: Difficulties of Identification and Typical Formation Models

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Speech and Computer (SPECOM 2020)

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Abstract

The paper deals with new research findings on pragmatic markers (PMs) use in spoken Russian. The study is based on two speech corpora: “One Day of Speech” (ORD, which contains mainly dialogues), and “Balanced Annotated Collection of Texts” (SAT, which contains only monologues). We explored two annotated subcorpora consisting of 321,504 tokens and 50,128 tokens respectively. The main results are as follows: 1) the extended frequency lists of PMs were formed; 2) PMs, that are frequently used in both types of speech, were identified (e.g., hesitation markers like tam ‘there’, tak ‘that way’), 3) the list of PMs, used primarily in monologue speech, was compiled (in this list there are such PMs as boundary ones znachit ‘well’, nu vot ‘well er’, vs’o ‘that’s all’); 4) the list of PMs, used primarily in dialogues, was made (among such PMs are, for example, “xeno”-markers takoj ‘like’, grit ‘says’ and meta-communicative markers like vidish’ ‘you know’, (ja) ne znaju ‘don’t know’). Particular attention was paid to the variability of pragmatic markers, as well as to complex cases of their identification. Finally, the most common models of pragmatic markers formation (for single-word and multi-word PMs) were revealed.

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Notes

  1. 1.

    The closest to the particles are “xeno”-markers, but they also differ from traditional particles, introducing someone else’s speech into the narrative (mol, de, deskat’), for example, due to the fact that the “atavisms” of grammatical meaning are retained predominantly: variability by gender and number (takoj/takaja/takie) or by face and number (gr’u, grit, grim, etc.) [7]. B. Fraser also includes “xeno”-markers to pragmatic markers, not to particles [17].

  2. 2.

    On the difficulties of part-of-speech tagging of corpus material, given the presence of a large number of pragmatic markers in it, which are only etymologically related to traditional parts of speech, see, for example: [14].

  3. 3.

    Such relationships between markers and outwardly corresponding full-valued lexical units are considered by B. Fraser as homophony [18].

  4. 4.

    Linguists have written more than once about the prospects of the scaling method when describing the fate of particular units in our language/speech, cf.: “Recently, the idea that it is advisable to abandon the “Procrustean bed” of a clear and uncompromising scheme and prefer the method quantitative assessment, according to which each linguistic phenomenon should be described in case of the place it occupies on the gradual transition scale ” [1: 89]. Pragmatic markers on their “way from classical lexemes” often go through the grammaticalization [15, 16, 19], cf.:

    • skazat’ – a verb in all the richness of its meanings and grammatical forms→skazhem as a parenthesis (ja zhe ne otlichu tak skazhem / tadzhika ot uzbeka) (frozen form, the result of grammaticalization)→(…) skazhem (…) as a PM, more often reflective (R) (tam slozhnaja publika / skazhem tak) or hesitative (H) (nu(:) / tam skazhem / *P nu / ne znaju / pajaet chto-to) (the result of pragmaticalization);

    • sejchas – an adverb with a number of meanings and a grammatical characteristic→shchas (usually in a reduced form) – interjection (Ja? Xa! Shchas pr’am!) (the result of grammaticalization)→shchas-shchas as a hesitative marker (H) (usually with multiple repetition, reduction) (tak / shchas-shchas-shchas-shchas / podozhdi) (the result of pragmaticalization).

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Acknowledgements

The presented research was supported by the Russian Science Foundation, project #18-18-00242 “Pragmatic Markers in Russian Everyday Speech”.

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Correspondence to Tatiana Sherstinova .

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Bogdanova-Beglarian, N., Blinova, O., Sherstinova, T., Gorbunova, D., Zaides, K., Popova, T. (2020). Pragmatic Markers in Dialogue and Monologue: Difficulties of Identification and Typical Formation Models. In: Karpov, A., Potapova, R. (eds) Speech and Computer. SPECOM 2020. Lecture Notes in Computer Science(), vol 12335. Springer, Cham. https://doi.org/10.1007/978-3-030-60276-5_7

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