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Automatic Prominence Classification in Swedish
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Speech Technology, CTT.
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Speech Technology, CTT.
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Music Acoustics. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Speech Technology, CTT.
2010 (English)In: Proceedings of Speech Prosody 2010, Workshop on Prosodic Prominence, Chicago, USA, 2010Conference paper, Published paper (Refereed)
Abstract [en]

This study aims at automatically classifying levels of acoustic prominence on a dataset of 200 Swedish sentences of read speech by one male native speaker. Each word in the sentences was categorized by four speech experts into one of three groups depending on the level of prominence perceived. Six acoustic features at a syllable level and seven features at a word level were used. Two machine learning algorithms, namely Support Vector Machines (SVM) and memory based Learning (MBL) were trained to classify the sentences into their respective classes. The MBL gave an average word level accuracy of 69.08% and the SVM gave an average accuracy of 65.17 % on the test set. These values were comparable with the average accuracy of the human annotators with respect to the average annotations. In this study, word duration was found to be the most important feature required for classifying prominence in Swedish read speech

Place, publisher, year, edition, pages
Chicago, USA, 2010.
Keyword [en]
Swedish prominence, SVM, MBL, syllable and word level features, word duration
National Category
Computer Science Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:kth:diva-52120OAI: oai:DiVA.org:kth-52120DiVA: diva2:465415
Conference
Speech Prosody 2010, Workshop on Prosodic Prominence, Chicago, USA
Note
tmh_import_11_12_14. QC 20111220Available from: 2011-12-14 Created: 2011-12-14 Last updated: 2012-11-23Bibliographically approved
In thesis
1. Bringing the avatar to life: Studies and developments in facial communication for virtual agents and robots
Open this publication in new window or tab >>Bringing the avatar to life: Studies and developments in facial communication for virtual agents and robots
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The work presented in this thesis comes in pursuit of the ultimate goal of building spoken and embodied human-like interfaces that are able to interact with humans under human terms. Such interfaces need to employ the subtle, rich and multidimensional signals of communicative and social value that complement the stream of words – signals humans typically use when interacting with each other.

The studies presented in the thesis concern facial signals used in spoken communication, and can be divided into two connected groups. The first is targeted towards exploring and verifying models of facial signals that come in synchrony with speech and its intonation. We refer to this as visual-prosody, and as part of visual-prosody, we take prominence as a case study. We show that the use of prosodically relevant gestures in animated faces results in a more expressive and human-like behaviour. We also show that animated faces supported with these gestures result in more intelligible speech which in turn can be used to aid communication, for example in noisy environments.

The other group of studies targets facial signals that complement speech. As spoken language is a relatively poor system for the communication of spatial information; since such information is visual in nature. Hence, the use of visual movements of spatial value, such as gaze and head movements, is important for an efficient interaction. The use of such signals is especially important when the interaction between the human and the embodied agent is situated – that is when they share the same physical space, and while this space is taken into account in the interaction.

We study the perception, the modelling, and the interaction effects of gaze and head pose in regulating situated and multiparty spoken dialogues in two conditions. The first is the typical case where the animated face is displayed on flat surfaces, and the second where they are displayed on a physical three-dimensional model of a face. The results from the studies show that projecting the animated face onto a face-shaped mask results in an accurate perception of the direction of gaze that is generated by the avatar, and hence can allow for the use of these movements in multiparty spoken dialogue.

Driven by these findings, the Furhat back-projected robot head is developed. Furhat employs state-of-the-art facial animation that is projected on a 3D printout of that face, and a neck to allow for head movements. Although the mask in Furhat is static, the fact that the animated face matches the design of the mask results in a physical face that is perceived to “move”.

We present studies that show how this technique renders a more intelligible, human-like and expressive face. We further present experiments in which Furhat is used as a tool to investigate properties of facial signals in situated interaction.

Furhat is built to study, implement, and verify models of situated and multiparty, multimodal Human-Machine spoken dialogue, a study that requires that the face is physically situated in the interaction environment rather than in a two-dimensional screen. It also has received much interest from several communities, and been showcased at several venues, including a robot exhibition at the London Science Museum. We present an evaluation study of Furhat at the exhibition where it interacted with several thousand persons in a multiparty conversation. The analysis of the data from the setup further shows that Furhat can accurately regulate multiparty interaction using gaze and head movements.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. xxvi, 96 p.
Series
Trita-CSC-A, ISSN 1653-5723 ; 2012:15
Keyword
Avatar, Speech Communication, Facial animation, Nonverbal, Social, Robot, Human-like, Face-to-face, Prosody, Pitch, Prominence, Furhat, Gaze, Head-pose, Dialogue, Interaction, Multimodal, Multiparty
National Category
Human Computer Interaction
Research subject
SRA - ICT
Identifiers
urn:nbn:se:kth:diva-105605 (URN)978-91-7501-551-4 (ISBN)
Public defence
2012-12-07, F3, Lindstedtsvägen 26, KTH, Stockholm, 13:30 (English)
Opponent
Supervisors
Note

QC 20121123

Available from: 2012-11-23 Created: 2012-11-22 Last updated: 2012-12-10Bibliographically approved

Open Access in DiVA

No full text

Other links

http://www.speech.kth.se/prod/publications/files/3403.pdf

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