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Cues to perceived functions of acted and spontaneous feedback expressions
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology. (Tal)
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology. (Tal)ORCID iD: 0000-0002-0397-6442
2012 (English)In: Proceedings of theInterdisciplinary Workshop on Feedback Behaviors in Dialog, 2012, p. 53-56Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

We present a two step study where the first part aims to determine the phonemic prior bias (conditioned on “ah”, “m-hm”, “m-m”, “n-hn”, “oh”, “okay”, “u-hu”, “yeah” and “yes”) in subjects perception of six feedback functions (acknowledgment, continuer, disagreement, surprise, enthusiasm and uncertainty). The results showed a clear phonemic prior bias for some tokens, e.g “ah” and “oh” is commonly interpreted as surprise but “yeah” and “yes” less so. The second part aims to examine determinants to judged typicality, or graded structure, within the six functions of “okay”. Typicality was correlated to four determinants: prosodic central tendency within the function (CT); phonemic prior bias as an approximation to frequency instantiation (FI), the posterior i.e. CT x FI and judged Ideality (ID), i.e. similarity to ideals associated with the goals served by its function. The results tentatively suggests that acted expressions are more effectively communicated and that the functions of feedback to a greater extent constitute goal-based categories determined by ideals and to a lesser extent a taxonomy determined by CT and FI. However, it is possible to automatically predict typicality with a correlation of r = 0.52 via the posterior.

Place, publisher, year, edition, pages
2012. p. 53-56
Keywords [en]
feedback, functions of feedback, goal driven categories, taxonomy
National Category
Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:kth:diva-102333OAI: oai:DiVA.org:kth-102333DiVA, id: diva2:552374
Conference
The Interdisciplinary Workshop on Feedback Behaviors in Dialog
Projects
SAMSYNTIURO
Funder
Swedish Research Council, 2009-4291EU, European Research Council, FP7 – 248314ICT - The Next Generation
Note

QC 20120914

Available from: 2012-09-14 Created: 2012-09-14 Last updated: 2024-03-18Bibliographically approved
In thesis
1. Modelling Paralinguistic Conversational Interaction: Towards social awareness in spoken human-machine dialogue
Open this publication in new window or tab >>Modelling Paralinguistic Conversational Interaction: Towards social awareness in spoken human-machine dialogue
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Parallel with the orthographic streams of words in conversation are multiple layered epiphenomena, short in duration and with a communicativepurpose. These paralinguistic events regulate the interaction flow via gaze,gestures and intonation. This thesis focus on how to compute, model, discoverand analyze prosody and it’s applications for spoken dialog systems.Specifically it addresses automatic classification and analysis of conversationalcues related to turn-taking, brief feedback, affective expressions, their crossrelationshipsas well as their cognitive and neurological basis. Techniques areproposed for instantaneous and suprasegmental parameterization of scalarand vector valued representations of fundamental frequency, but also intensity and voice quality. Examples are given for how to engineer supervised learned automata’s for off-line processing of conversational corpora as well as for incremental on-line processing with low-latency constraints suitable as detector modules in a responsive social interface. Specific attention is given to the communicative functions of vocal feedback like "mhm", "okay" and "yeah, that’s right" as postulated by the theories of grounding, emotion and a survey on laymen opinions. The potential functions and their prosodic cues are investigated via automatic decoding, data-mining, exploratory visualization and descriptive measurements.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. p. xiv, 86
Series
Trita-CSC-A, ISSN 1653-5723 ; 2012:08
National Category
Language Technology (Computational Linguistics)
Identifiers
urn:nbn:se:kth:diva-102335 (URN)978-91-7501-467-8 (ISBN)
Public defence
2012-09-28, Sal F3, Lindstedtsvägen 26, KTH, Stockholm, 13:00 (English)
Opponent
Supervisors
Note

QC 20120914

Available from: 2012-09-14 Created: 2012-09-14 Last updated: 2022-06-24Bibliographically approved

Open Access in DiVA

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Other links

http://www.cs.utep.edu/feedback/proceedings/full-proceedings.pdf

Authority records

Neiberg, DanielGustafson, Joakim

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Output format
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