Prosodic Patterns in Spontaneous and Pseudo-Spontaneous Speech (a comparative study based on the German language)

Cover Page

Cite item

Abstract

The aim of the present study is to identify differences between spontaneous and pseudo-spontaneous speech based on the measurement of prosodic characteristics, in particular fundamental frequency, sound intensity, speech rate, and pause parameters, in the speech of a single speaker in different communicative situations. The material included recordings of a German-speaking speaker in the formats of an interview and a popular science blog. The acoustic analysis method was applied using the Praat and SRM software. The study revealed significant differences in prosodic features, which support the classification of pseudo-spontaneous speech as a distinct speech type. The findings are relevant for phonostylistics, speech pragmatics, and automatic speech analysis.

About the authors

Marianna Viktorovna Popova

Moscow State Linguistic University

Author for correspondence.
Email: neunerin@gmail.com

PhD in Philology, Associate Professor at the Department of German Phonetics, Faculty of the German Language

Russian Federation

Anastasiya Dmitrievna Frolova

Moscow State Linguistic University

Email: gmuft@yandex.ru

Lecturer at the Department of German Phonetics, Faculty of the German Language

Russian Federation

References

  1. Nadeina, T. M. (2004). Prosodicheskaya organizatsiya rechi kak faktor rechevogo vozdeistviya = Prosodic organization of speech as a factor of speech impact : abstract of Senior Doctoral thesis in Philology. Moscow. (In Russ.)
  2. Popova, M. V. (2021). Comparative analysis of the concepts of “prosody”, “intonation” and related special terms in linguistics. Vestnik of Moscow State University. Humanities, 11(853), 150–160. (In Russ.)
  3. Velikaya, E. V. (2009). Prosodiya v stilevoi differentsiatsii yazyka = Prosody in the stylistic differentiation of language: monograph. Moscow: Prometei. (In Russ.)
  4. Dunashova, A. V. (2021). Stylistic variation of prosodic patterns of a linguistic persona. Theoretical and Applied Linguistics, 7(1), 22–30. (In Russ.)
  5. Dergacheva, L. A. (2014). Linguostylistic features of quasi-spontaneous speech. Bulletin of Tver State University. Philology, 2, 201–207. (In Russ.)
  6. Potapova, R. K., Potapov, V. V. (2006). Yazyk, rech’, lichnost’ = Language, speech, identity. Moscow: Yazyki slavyanskoi kul’tury. (In Russ.)
  7. Galyashina, E. I. (2003). Ustanovlenie fakta predvaritel’noi podgotovki pis’mennykh i ustnykh tekstov = Establishing the fact of preliminary preparation of written and oral texts: Method. Recommendations. Moscow: GU EKTS MVD Rossii. (In Russ.)
  8. Shevchenko, T. I. et al. (2017). Metody analiza zvuchashchei rechi: novye izmereniya i rezul’taty = Methods of analysis of sounding speech: new measurements and results. Dubna: Feniks+. (In Russ.)
  9. Freidina, E. L. et al. (2013). Prosodiya publichnoi rechi = Prosody of public speech: monograph. Moscow: Prometei. (In Russ.)
  10. Lobanov, B. M., Zhitko, V. A. (2021). Method for Statistical Estimation of the Prosodic Parameters of Speech Tempo (based on Russian speech). In Komp`yuternaya lingvistika i intellektual`ny`e texnologii (issue 20, pp. 1120–1129): Proceedings of the international scientific conference "Dialog". Moscow: Russian State University for the Humanities. (In Russ.)
  11. Lorenzen, R. (2004). Eine akustisch-phonetische Untersuchung zur Stimmverstellung. Kiel.
  12. Pfitzinger, H. (1999). Local Speech Rate Perception in German Speech. In 14th International Congress of Phonetic Sciences (pp. 893–896). San Francisco.

Supplementary files

Supplementary Files
Action
1. JATS XML


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).