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Publications (10 of 102) Show all publications
Kontogiorgos, D., Avramova, V., Alexanderson, S., Jonell, P., Oertel, C., Beskow, J., . . . Gustafson, J. (2018). A Multimodal Corpus for Mutual Gaze and Joint Attention in Multiparty Situated Interaction. In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018): . Paper presented at International Conference on Language Resources and Evaluation (LREC 2018) (pp. 119-127). Paris
Open this publication in new window or tab >>A Multimodal Corpus for Mutual Gaze and Joint Attention in Multiparty Situated Interaction
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2018 (English)In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Paris, 2018, p. 119-127Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we present a corpus of multiparty situated interaction where participants collaborated on moving virtual objects on a large touch screen. A moderator facilitated the discussion and directed the interaction. The corpus contains recordings of a variety of multimodal data, in that we captured speech, eye gaze and gesture data using a multisensory setup (wearable eye trackers, motion capture and audio/video). Furthermore, in the description of the multimodal corpus, we investigate four different types of social gaze: referential gaze, joint attention, mutual gaze and gaze aversion by both perspectives of a speaker and a listener. We annotated the groups’ object references during object manipulation tasks and analysed the group’s proportional referential eye-gaze with regards to the referent object. When investigating the distributions of gaze during and before referring expressions we could corroborate the differences in time between speakers’ and listeners’ eye gaze found in earlier studies. This corpus is of particular interest to researchers who are interested in social eye-gaze patterns in turn-taking and referring language in situated multi-party interaction.

Place, publisher, year, edition, pages
Paris: , 2018
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-230238 (URN)979-10-95546-00-9 (ISBN)
Conference
International Conference on Language Resources and Evaluation (LREC 2018)
Note

QC 20180614

Available from: 2018-06-13 Created: 2018-06-13 Last updated: 2018-06-14Bibliographically approved
Jonell, P., Oertel, C., Kontogiorgos, D., Beskow, J. & Gustafson, J. (2018). Crowdsourced Multimodal Corpora Collection Tool. In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018): . Paper presented at The Eleventh International Conference on Language Resources and Evaluation (LREC 2018) (pp. 728-734). Paris
Open this publication in new window or tab >>Crowdsourced Multimodal Corpora Collection Tool
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2018 (English)In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Paris, 2018, p. 728-734Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, more and more multimodal corpora have been created. To our knowledge there is no publicly available tool which allows for acquiring controlled multimodal data of people in a rapid and scalable fashion. We therefore are proposing (1) a novel tool which will enable researchers to rapidly gather large amounts of multimodal data spanning a wide demographic range, and (2) an example of how we used this tool for corpus collection of our "Attentive listener'' multimodal corpus. The code is released under an Apache License 2.0 and available as an open-source repository, which can be found at https://github.com/kth-social-robotics/multimodal-crowdsourcing-tool. This tool will allow researchers to set-up their own multimodal data collection system quickly and create their own multimodal corpora. Finally, this paper provides a discussion about the advantages and disadvantages with a crowd-sourced data collection tool, especially in comparison to a lab recorded corpora.

Place, publisher, year, edition, pages
Paris: , 2018
National Category
Engineering and Technology
Research subject
Computer Science
Identifiers
urn:nbn:se:kth:diva-230236 (URN)979-10-95546-00-9 (ISBN)
Conference
The Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
Note

QC 20180618

Available from: 2018-06-13 Created: 2018-06-13 Last updated: 2018-06-18Bibliographically approved
Kontogiorgos, D., Sibirtseva, E., Pereira, A., Skantze, G. & Gustafson, J. (2018). Multimodal reference resolution in collaborative assembly tasks. In: : . Paper presented at Workshop on Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction. ACM Digital Library
Open this publication in new window or tab >>Multimodal reference resolution in collaborative assembly tasks
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2018 (English)Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
ACM Digital Library, 2018
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-235547 (URN)10.1145/3279972.3279976 (DOI)
Conference
Workshop on Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction
Note

QC 20181009

Available from: 2018-09-29 Created: 2018-09-29 Last updated: 2018-10-09Bibliographically approved
Malisz, Z., Berthelsen, H., Beskow, J. & Gustafson, J. (2017). Controlling prominence realisation in parametric DNN-based speech synthesis. In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2017: . Paper presented at 18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, Stockholm, Sweden, 20 August 2017 through 24 August 2017 (pp. 1079-1083). International Speech Communication Association, 2017
Open this publication in new window or tab >>Controlling prominence realisation in parametric DNN-based speech synthesis
2017 (English)In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, International Speech Communication Association , 2017, Vol. 2017, p. 1079-1083Conference paper, Published paper (Refereed)
Abstract [en]

This work aims to improve text-To-speech synthesis forWikipedia by advancing and implementing models of prosodic prominence. We propose a new system architecture with explicit prominence modeling and test the first component of the architecture. We automatically extract a phonetic feature related to prominence from the speech signal in the ARCTIC corpus. We then modify the label files and train an experimental TTS system based on the feature using Merlin, a statistical-parametric DNN-based engine. Test sentences with contrastive prominence on the word-level are synthesised and separate listening tests a) evaluating the level of prominence control in generated speech, and b) naturalness, are conducted. Our results show that the prominence feature-enhanced system successfully places prominence on the appropriate words and increases perceived naturalness relative to the baseline.

Place, publisher, year, edition, pages
International Speech Communication Association, 2017
Series
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, ISSN 2308-457X
Keywords
Deep neural networks, Prosodic prominence, Speech synthesis
National Category
Language Technology (Computational Linguistics)
Identifiers
urn:nbn:se:kth:diva-222092 (URN)10.21437/Interspeech.2017-1355 (DOI)2-s2.0-85039164235 (Scopus ID)
Conference
18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, Stockholm, Sweden, 20 August 2017 through 24 August 2017
Note

QC 20180131

Available from: 2018-01-31 Created: 2018-01-31 Last updated: 2018-01-31Bibliographically approved
Szekely, E., Mendelson, J. & Gustafson, J. (2017). Synthesising uncertainty: The interplay of vocal effort and hesitation disfluencies. In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH: . Paper presented at 18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, Stockholm, Sweden, 20 August 2017 through 24 August 2017 (pp. 804-808). International Speech Communication Association, 2017
Open this publication in new window or tab >>Synthesising uncertainty: The interplay of vocal effort and hesitation disfluencies
2017 (English)In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, International Speech Communication Association , 2017, Vol. 2017, p. 804-808Conference paper (Refereed)
Abstract [en]

As synthetic voices become more flexible, and conversational systems gain more potential to adapt to the environmental and social situation, the question needs to be examined, how different modifications to the synthetic speech interact with each other and how their specific combinations influence perception. This work investigates how the vocal effort of the synthetic speech together with added disfluencies affect listeners' perception of the degree of uncertainty in an utterance. We introduce a DNN voice built entirely from spontaneous conversational speech data and capable of producing a continuum of vocal efforts, prolongations and filled pauses with a corpus-based method. Results of a listener evaluation indicate that decreased vocal effort, filled pauses and prolongation of function words increase the degree of perceived uncertainty of conversational utterances expressing the speaker's beliefs. We demonstrate that the effect of these three cues are not merely additive, but that interaction effects, in particular between the two types of disfluencies and between vocal effort and prolongations need to be considered when aiming to communicate a specific level of uncertainty. The implications of these findings are relevant for adaptive and incremental conversational systems using expressive speech synthesis and aspiring to communicate the attitude of uncertainty.

Place, publisher, year, edition, pages
International Speech Communication Association, 2017
Series
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, ISSN 2308-457X
Keywords
Conversational Systems, Disfluencies, Speech Synthesis, Uncertainty, Vocal Effort
National Category
Communication Studies
Identifiers
urn:nbn:se:kth:diva-220749 (URN)10.21437/Interspeech.2017-1507 (DOI)2-s2.0-85039172286 (Scopus ID)
Conference
18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, Stockholm, Sweden, 20 August 2017 through 24 August 2017
Note

QC 20180105

Available from: 2018-01-05 Created: 2018-01-05 Last updated: 2018-01-05Bibliographically approved
Oertel, C., Jonell, P., Haddad, K. E., Szekely, E. & Gustafson, J. (2017). Using crowd-sourcing for the design of listening agents: Challenges and opportunities. In: ISIAA 2017 - Proceedings of the 1st ACM SIGCHI International Workshop on Investigating Social Interactions with Artificial Agents, Co-located with ICMI 2017: . Paper presented at 1st ACM SIGCHI International Workshop on Investigating Social Interactions with Artificial Agents, ISIAA 2017, Glasgow, United Kingdom, 13 November 2017 (pp. 37-38). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Using crowd-sourcing for the design of listening agents: Challenges and opportunities
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2017 (English)In: ISIAA 2017 - Proceedings of the 1st ACM SIGCHI International Workshop on Investigating Social Interactions with Artificial Agents, Co-located with ICMI 2017, Association for Computing Machinery (ACM), 2017, p. 37-38Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we are describing how audio-visual corpora recordings using crowd-sourcing techniques can be used for the audio-visual synthesis of attitudinal non-verbal feedback expressions for virtual agents. We are discussing the limitations of this approach as well as where we see the opportunities for this technology.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2017
Keywords
Artificial listener, Listening agent, Multimodal behaviour generation
National Category
Interaction Technologies
Identifiers
urn:nbn:se:kth:diva-222507 (URN)10.1145/3139491.3139499 (DOI)2-s2.0-85041230172 (Scopus ID)9781450355582 (ISBN)
Conference
1st ACM SIGCHI International Workshop on Investigating Social Interactions with Artificial Agents, ISIAA 2017, Glasgow, United Kingdom, 13 November 2017
Note

QC 20180212

Available from: 2018-02-12 Created: 2018-02-12 Last updated: 2018-02-12Bibliographically approved
Edlund, J. & Gustafson, J. (2016). Hidden resources - Strategies to acquire and exploit potential spoken language resources in national archives. In: Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016: . Paper presented at 10th International Conference on Language Resources and Evaluation, LREC 2016, 23 May 2016 through 28 May 2016 (pp. 4531-4534). European Language Resources Association (ELRA)
Open this publication in new window or tab >>Hidden resources - Strategies to acquire and exploit potential spoken language resources in national archives
2016 (English)In: Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016, European Language Resources Association (ELRA) , 2016, p. 4531-4534Conference paper, Published paper (Refereed)
Abstract [en]

In 2014, the Swedish government tasked a Swedish agency, The Swedish Post and Telecom Authority (PTS), with investigating how to best create and populate an infrastructure for spoken language resources (Ref N2014/2840/ITP). As a part of this work, the department of Speech, Music and Hearing at KTH Royal Institute of Technology have taken inventory of existing potential spoken language resources, mainly in Swedish national archives and other governmental or public institutions. In this position paper, key priorities, perspectives, and strategies that may be of general, rather than Swedish, interest are presented. We discuss broad types of potential spoken language resources available; to what extent these resources are free to use; and thirdly the main contribution: strategies to ensure the continuous acquisition of spoken language resources in a manner that facilitates speech and speech technology research.

Place, publisher, year, edition, pages
European Language Resources Association (ELRA), 2016
Keywords
National archives, Oral history, Speech, Hidden resources, Public institution, Royal Institute of Technology, Speech technology, Spoken languages, Swedish government, Audition
National Category
General Language Studies and Linguistics
Identifiers
urn:nbn:se:kth:diva-222949 (URN)2-s2.0-85037133240 (Scopus ID)9782951740891 (ISBN)
Conference
10th International Conference on Language Resources and Evaluation, LREC 2016, 23 May 2016 through 28 May 2016
Note

QC 20180327

Available from: 2018-03-27 Created: 2018-03-27 Last updated: 2018-05-24Bibliographically approved
Johansson, M., Hori, T., Skantze, G., Hothker, A. & Gustafson, J. (2016). Making Turn-Taking Decisions for an Active Listening Robot for Memory Training. In: SOCIAL ROBOTICS, (ICSR 2016): . Paper presented at 8th International Conference on Social Robotics (ICSR), NOV 01-03, 2016, Kansas City, MO (pp. 940-949). Springer
Open this publication in new window or tab >>Making Turn-Taking Decisions for an Active Listening Robot for Memory Training
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2016 (English)In: SOCIAL ROBOTICS, (ICSR 2016), Springer, 2016, p. 940-949Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we present a dialogue system and response model that allows a robot to act as an active listener, encouraging users to tell the robot about their travel memories. The response model makes a combined decision about when to respond and what type of response to give, in order to elicit more elaborate descriptions from the user and avoid non-sequitur responses. The model was trained on human-robot dialogue data collected in a Wizard-of-Oz setting, and evaluated in a fully autonomous version of the same dialogue system. Compared to a baseline system, users perceived the dialogue system with the trained model to be a significantly better listener. The trained model also resulted in dialogues with significantly fewer mistakes, a larger proportion of user speech and fewer interruptions.

Place, publisher, year, edition, pages
Springer, 2016
Series
Lecture Notes in Artificial Intelligence, ISSN 0302-9743 ; 9979
Keywords
Turn-taking, Active listening, Social robotics, Memory training
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-200064 (URN)10.1007/978-3-319-47437-3_92 (DOI)000389816500092 ()2-s2.0-84992499074 (Scopus ID)978-3-319-47437-3 (ISBN)978-3-319-47436-6 (ISBN)
Conference
8th International Conference on Social Robotics (ICSR), NOV 01-03, 2016, Kansas City, MO
Note

QC 20170125

Available from: 2017-01-25 Created: 2017-01-20 Last updated: 2018-01-13Bibliographically approved
Edlund, J., Tånnander, C. & Gustafson, J. (2015). Audience response system-based assessment for analysis-by-synthesis. In: Proc. of ICPhS 2015: . Paper presented at ICPhS 2015. ICPhS
Open this publication in new window or tab >>Audience response system-based assessment for analysis-by-synthesis
2015 (English)In: Proc. of ICPhS 2015, ICPhS , 2015Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
ICPhS, 2015
National Category
Computer Sciences Language Technology (Computational Linguistics)
Identifiers
urn:nbn:se:kth:diva-180399 (URN)
Conference
ICPhS 2015
Note

QC 20160317

Available from: 2016-01-13 Created: 2016-01-13 Last updated: 2018-01-10Bibliographically approved
Meena, R., David Lopes, J., Skantze, G. & Gustafson, J. (2015). Automatic Detection of Miscommunication in Spoken Dialogue Systems. In: Proceedings of 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL): . Paper presented at 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL) (pp. 354-363).
Open this publication in new window or tab >>Automatic Detection of Miscommunication in Spoken Dialogue Systems
2015 (English)In: Proceedings of 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), 2015, p. 354-363Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present a data-driven approach for detecting instances of miscommunication in dialogue system interactions. A range of generic features that are both automatically extractable and manually annotated were used to train two models for online detection and one for offline analysis. Online detection could be used to raise the error awareness of the system, whereas offline detection could be used by a system designer to identify potential flaws in the dialogue design. In experimental evaluations on system logs from three different dialogue systems that vary in their dialogue strategy, the proposed models performed substantially better than the majority class baseline models.

National Category
Computer Sciences Language Technology (Computational Linguistics)
Identifiers
urn:nbn:se:kth:diva-180406 (URN)2-s2.0-84988311476 (Scopus ID)
Conference
16th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)
Note

QC 20160120

Available from: 2016-01-13 Created: 2016-01-13 Last updated: 2018-01-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0397-6442

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