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H2020Individual fellowship2018–2020

HA-HA · LAUGHTER IN CONVERSATION: ENHANCING THE NATURALNESS OF DIALOGUE SYSTEMS

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2018-11-01 → 2020-11-07
EU contribution
€159,461
Participants
1
Scheme
MSCA-IF-EF-ST

Lines connect the coordinator with its partners.

Results in brief

LAUGHTER IN CONVERSATION: ENHANCING THE NATURALNESS OF DIALOGUE SYSTEMS

With smartphones and computers being an integral component of nowadays life, people interact more and more with their devices. Although recently there have been some important advances in speech technology, such as better automatic recognition and synthesis, in terms of conversational aspects, automatic systems still do not exploit the richness of cues found in human communication. In this project we explored how one of the most encountered non-verbal vocalisations in human conversations, laughter, may be integrated in a spoken dialogue system. In order for this to be achieved, we first performed a quantitative analysis of laughter use in human interaction, by taking into account factors such as the level of analysis or the influence of the conversational partner. Next, we studied acoustic cues able to discriminate laughter from speech and developed an automatic laughter detection system based on these. Finally, we conducted a perceptual experiment with adult participants asking them to judge the outcome of conversation between a virtual agent and a person, when the agent employed laughter or not.

Data: CORDIS, © European Union

Project objective

With the wide-scale adoption of speech-based applications, the research community has started focusing on ways to improve naturalness and expressiveness of human-machine interactions. Among the directions pursued, the study of paralinguistic phenomena in conversation plays an important role. This project proposes to investigate conversational laughter, both from a fundamental research perspective as well as from an application viewpoint. The addressed research question concerns the context in which social laughter occurs, in particular the use of acoustic-prosodic cues in marking it. The findings of this investigation will directly feed into a spoken dialogue system, with the aim of increasing its perceived naturalness. In a first step, phrase- and turn-level analyses will be performed to identify the range of cues used by speakers to mark the use of laughter in conversation. Next, state-of-the-art signal processing methods combined with prosodic information will be used to automatically detect and segment laughter. This will allow the analysis of a larger number of conversational corpora which would, in turn, improve the generalizability of the results. Finally, a laughter-enhanced dialogue system will be implemented and its naturalness will be tested through perception experiments. It is expected that the laughter-enhanced system will be perceived more natural and that documented gender differences found in the production of laughter will be found also in its perception.

Original text from CORDIS.

Participants

  • UNIVERSITAET BIELEFELD · BielefeldCoordinatorGermany

Links

Data: CORDIS, © European Union