Pauses, gaps and overlaps in conversations
By Mattias Heldner, Jens Edlund. 2010
574 citations recorded by the source corpus.
This paper explores durational aspects of pauses gaps and overlaps in three different conversational corpora with a view to challenge claims about precision timing in turn-taking Distributions of p ...
Subfields: Artificial Intelligence, Language and Linguistics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Wei-Ning Hsu
- Yossi Adi
- Jade Copet
- Emmanuel Dupoux
- Tu Nguyen
- Evgeny Kharitonov
- Abdel-rahman Mohamed
- Gabriel Synnaeve
In Language and Linguistics
- Gabriel Skantze
- Jennifer Cole
- Francisco Torreira
- Emmanuel Dupoux
- Wei-Ning Hsu
- Stephen C. Levinson
- Marianne Gullberg
- Noah D. Goodman
Citations in the corpus
- Generative Spoken Dialogue Language Modeling (2022, background): “It is interesting to note that all models, except DLM-1, manage to capture the empirical fact that intra-turn pauses tend to be longer than between-turn gaps (Brady, 1968; Ten Bosch et al., 2005; Heldner and Edlund, 2010).”
- Timing in turn-taking and its implications for processing models of language (2015, methodology): “%) of all turn transitions across corpora take place in under 200 ms (Heldner and Edlund, 2010, p. 563).”
- Prosody in context: a review (2015, background): “Moreover, some prosodic functions are specific to interactive dialogue, such management of turn-taking or floor-holding strategies (Heldner & Edlund, 2010; Local, Kelly, & Wells, 1986; Selting, 2000), so interactions involving these prosodic patterns must be investigated with interactive speech…”
- Towards a General, Continuous Model of Turn-taking in Spoken Dialogue using LSTM Recurrent Neural Networks (2017, background): “However, in studies of human-human dialogue it is clear that overlaps are fairly frequent (Heldner and Edlund, 2010).”
- Investigating Speech Features for Continuous Turn-Taking Prediction Using LSTMs (2018, unknown): “500ms has been identified in the literature as being a common pause threshold in many commercial speech technologies [11].”