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Can We Detect Irony in Speech Using Phonetic Characteristics Only? – Looking for a Methodology of Analysis. / Skrelin, Pavel; Kochetkova, Uliana; Evdokimova, Vera; Novoselova, Daria.

Speech and Computer - 22nd International Conference, SPECOM 2020, Proceedings. ред. / Alexey Karpov; Rodmonga Potapova. Springer Nature, 2020. стр. 544-553 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 12335 LNAI).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Skrelin, P, Kochetkova, U, Evdokimova, V & Novoselova, D 2020, Can We Detect Irony in Speech Using Phonetic Characteristics Only? – Looking for a Methodology of Analysis. в A Karpov & R Potapova (ред.), Speech and Computer - 22nd International Conference, SPECOM 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 12335 LNAI, Springer Nature, стр. 544-553, 22nd International Conference on Speech and Computer, St. Petersburg, Российская Федерация, 7/10/20. https://doi.org/10.1007/978-3-030-60276-5_52

APA

Skrelin, P., Kochetkova, U., Evdokimova, V., & Novoselova, D. (2020). Can We Detect Irony in Speech Using Phonetic Characteristics Only? – Looking for a Methodology of Analysis. в A. Karpov, & R. Potapova (Ред.), Speech and Computer - 22nd International Conference, SPECOM 2020, Proceedings (стр. 544-553). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 12335 LNAI). Springer Nature. https://doi.org/10.1007/978-3-030-60276-5_52

Vancouver

Skrelin P, Kochetkova U, Evdokimova V, Novoselova D. Can We Detect Irony in Speech Using Phonetic Characteristics Only? – Looking for a Methodology of Analysis. в Karpov A, Potapova R, Редакторы, Speech and Computer - 22nd International Conference, SPECOM 2020, Proceedings. Springer Nature. 2020. стр. 544-553. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-60276-5_52

Author

Skrelin, Pavel ; Kochetkova, Uliana ; Evdokimova, Vera ; Novoselova, Daria. / Can We Detect Irony in Speech Using Phonetic Characteristics Only? – Looking for a Methodology of Analysis. Speech and Computer - 22nd International Conference, SPECOM 2020, Proceedings. Редактор / Alexey Karpov ; Rodmonga Potapova. Springer Nature, 2020. стр. 544-553 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{8599581fc6824bdd83161f57642cbd7d,
title = "Can We Detect Irony in Speech Using Phonetic Characteristics Only? – Looking for a Methodology of Analysis",
abstract = "The current paper aims to investigate the perception of Russian ironic laboratory speech and to develop a methodological basis for the further research on perceptually relevant acoustic cues of irony. On the first stage of analysis we created short monologues and dialogues including ironic and homonymous non-ironic sentences. Two Russian native male speakers read this material. The recording was accomplished in a sound booth. Then, randomized fragments of the recordings were suggested to native listeners in an auditory perception experiment. The mean intensity, duration of the stressed vowel and F0 range in the reliably identified target fragments were analyzed, as well as functional intonation models in terms of the system suggested by E. Bryzgunova. The results showed that the listeners are able to detect irony without any contextual or lexical marker of it. The acoustic analysis of the reliably identified stimuli demonstrated the difference in intensity level and stressed vowel duration between ironic and non-ironic utterances. The obtained results allow creating a methodology of data collection and validation for the construction of ironic speech corpus and its analysis. They may also have applications in teaching Russian as a second language, human-machine communication and improving natural language processing systems.",
keywords = "Acoustic analysis, Auditory perception experiment, Intensity, Intonation models, Irony, Phonetics, Pitch",
author = "Pavel Skrelin and Uliana Kochetkova and Vera Evdokimova and Daria Novoselova",
note = "Funding Information: This research was supported by the RFBR grant ? 20-012-00552. Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 22nd International Conference on Speech and Computer, SPECOM 2020 ; Conference date: 07-10-2020 Through 09-10-2020",
year = "2020",
doi = "10.1007/978-3-030-60276-5_52",
language = "English",
isbn = "9783030602758",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "544--553",
editor = "Alexey Karpov and Rodmonga Potapova",
booktitle = "Speech and Computer - 22nd International Conference, SPECOM 2020, Proceedings",
address = "Germany",
url = "http://specom.nw.ru/2020/program/SPECOM-ICR2020-Conference-Program-06102020.pdf",

}

RIS

TY - GEN

T1 - Can We Detect Irony in Speech Using Phonetic Characteristics Only? – Looking for a Methodology of Analysis

AU - Skrelin, Pavel

AU - Kochetkova, Uliana

AU - Evdokimova, Vera

AU - Novoselova, Daria

N1 - Funding Information: This research was supported by the RFBR grant ? 20-012-00552. Publisher Copyright: © 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - The current paper aims to investigate the perception of Russian ironic laboratory speech and to develop a methodological basis for the further research on perceptually relevant acoustic cues of irony. On the first stage of analysis we created short monologues and dialogues including ironic and homonymous non-ironic sentences. Two Russian native male speakers read this material. The recording was accomplished in a sound booth. Then, randomized fragments of the recordings were suggested to native listeners in an auditory perception experiment. The mean intensity, duration of the stressed vowel and F0 range in the reliably identified target fragments were analyzed, as well as functional intonation models in terms of the system suggested by E. Bryzgunova. The results showed that the listeners are able to detect irony without any contextual or lexical marker of it. The acoustic analysis of the reliably identified stimuli demonstrated the difference in intensity level and stressed vowel duration between ironic and non-ironic utterances. The obtained results allow creating a methodology of data collection and validation for the construction of ironic speech corpus and its analysis. They may also have applications in teaching Russian as a second language, human-machine communication and improving natural language processing systems.

AB - The current paper aims to investigate the perception of Russian ironic laboratory speech and to develop a methodological basis for the further research on perceptually relevant acoustic cues of irony. On the first stage of analysis we created short monologues and dialogues including ironic and homonymous non-ironic sentences. Two Russian native male speakers read this material. The recording was accomplished in a sound booth. Then, randomized fragments of the recordings were suggested to native listeners in an auditory perception experiment. The mean intensity, duration of the stressed vowel and F0 range in the reliably identified target fragments were analyzed, as well as functional intonation models in terms of the system suggested by E. Bryzgunova. The results showed that the listeners are able to detect irony without any contextual or lexical marker of it. The acoustic analysis of the reliably identified stimuli demonstrated the difference in intensity level and stressed vowel duration between ironic and non-ironic utterances. The obtained results allow creating a methodology of data collection and validation for the construction of ironic speech corpus and its analysis. They may also have applications in teaching Russian as a second language, human-machine communication and improving natural language processing systems.

KW - Acoustic analysis

KW - Auditory perception experiment

KW - Intensity

KW - Intonation models

KW - Irony

KW - Phonetics

KW - Pitch

UR - http://www.scopus.com/inward/record.url?scp=85092889586&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/aaa9eee9-7e52-3412-885f-b002301c62df/

U2 - 10.1007/978-3-030-60276-5_52

DO - 10.1007/978-3-030-60276-5_52

M3 - Conference contribution

AN - SCOPUS:85092889586

SN - 9783030602758

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 544

EP - 553

BT - Speech and Computer - 22nd International Conference, SPECOM 2020, Proceedings

A2 - Karpov, Alexey

A2 - Potapova, Rodmonga

PB - Springer Nature

T2 - 22nd International Conference on Speech and Computer

Y2 - 7 October 2020 through 9 October 2020

ER -

ID: 70314230