This paper deals with acoustic properties of backchannels – those turns within a dialogue which do not convey information but signify that the speaker is listening to his/her interlocutor (uh-huh, hm etc.). The research is based on a Russian corpus of dialogue speech, SibLing, a part of which (339 min of speech) was manually segmented into backchannels and non-backchannels. Then, a number of acoustic parameters was calculated: duration, intensity, fundamental frequency, and pause duration. Our data have shown that in Russian speech backchannels are shorter and have lower loudness and pitch than non-backchannels. After that, two classifiers were tested: CART and SVM. The highest efficiency was achieved using SVM (F 1 = 0.651) and the following feature set: duration, maximum fundamental frequency, melodic slope. The most valuable feature was duration.
Original languageEnglish
Title of host publicationSpeech and Computer - 22nd International Conference, SPECOM 2020, Proceedings
Subtitle of host publication22nd International Conference, SPECOM 2020, St. Petersburg, Russia, October 7–9, 2020, Proceedings
EditorsAlexey Karpov, Rodmonga Potapova
Place of PublicationCham
PublisherSpringer Nature
Pages204-213
Number of pages10
ISBN (Electronic)978-3-030-60276-5
ISBN (Print)978-3-030-60275-8
DOIs
StatePublished - 2020
Event22nd International Conference on Speech and Computer - St. Petersburg, Russia => Online, St. Petersburg, Russian Federation
Duration: 7 Oct 20209 Oct 2020
http://specom.nw.ru/2020/program/SPECOM-ICR2020-Conference-Program-06102020.pdf

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12335 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Speech and Computer
Abbreviated titleSPECOM 2020
Country/TerritoryRussian Federation
CitySt. Petersburg
Period7/10/209/10/20
Internet address

    Research areas

  • Backchannel, Dialogue speech, Russian, Speech acoustics, Turn-taking

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

ID: 69802810