Automatic Detection of Backchannels in Russian Dialogue Speech

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review


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
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
ISBN (Electronic)978-3-030-60276-5
ISBN (Print)978-3-030-60275-8
StatePublished - 2020
Event22nd International Conference on Speech and Computer - St. Petersburg, Russia => Online, St. Petersburg, Russian Federation
Duration: 7 Oct 20209 Oct 2020

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


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


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