Associating children's non-verbal and verbal behaviour: Body movements, emotions, and laughter in a human-robot interaction

Batliner, Anton; Steidl, Stefan; Nöth, Elmar

doi:10.1109/icassp.2011.5947686

Cited by 13 publications

(5 citation statements)

References 4 publications

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“…Applications of the research area include interactive and communicative robots [1], [2]; diagnosis, monitoring, and screening of diseases and speech disorders [3] such as Parkinson's disease [4], [5]. Recent paralinguistic challenges introduce biomedical corpora e. g. for autism detection/diagnosis [6], and depression level prediction [7], [8] in order to help advance the field by providing transparency and comparability with state-of-the-art studies.…”

mentioning

confidence: 99%

Random Discriminative Projection Based Feature Selection with Application to Conflict Recognition

Kaya

Ozkaptan

Salah

et al. 2015

IEEE Signal Process. Lett.

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Abstract-Computational paralinguistics deals with underlying meaning of the verbal messages, which is of interest in manifold applications ranging from intelligent tutoring systems to affect sensitive robots. The state-of-the-art pipeline of paralinguistic speech analysis utilizes brute-force feature extraction, and the features need to be tailored according to the relevant task. In this work, we extend a recent discriminative projection based feature selection method using the power of stochasticity to overcome local minima and to reduce the computational complexity. The proposed approach assigns weights both to groups and to features individually in many randomly selected contexts and then combines them for a final ranking. The efficacy of the proposed method is shown in a recent paralinguistic challenge corpus to detect level of conflict in dyadic and group conversations. We advance the state-of-the-art in this corpus using the INTERSPEECH 2013 Challenge protocol.Index Terms-CCA, computational paralinguistics, discriminative projection, feature selection, random projection.

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mentioning

confidence: 99%

Random Discriminative Projection Based Feature Selection with Application to Conflict Recognition

Kaya

Ozkaptan

Salah

et al. 2015

IEEE Signal Process. Lett.

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“…Many kinds of research on the estimation of human intentions have been conducted for communication between robots and humans [5,6]. However, since these approaches are tracking individuals using cameras and microphones, these are not practical in a storytelling situation when the children's sitting positions are not fixed.…”

Section: Research On Automatic Estimations Of Human Intentionsmentioning

confidence: 99%

“…If the reaction evaluation is performed automatically using sensors, the improvement in educational activities is promoted with this improvement cycle. Conventionally, the automatic estimation of curiosity has been attempted by eyetracking [4] and multi-modal sensing using cameras and microphones [5,6]. However, these require expensive devices or strong restrictions on the location of users/devices.…”

Section: Introductionmentioning

confidence: 99%

A Curiosity Estimation in Storytelling with Picture Books for Children Using Wearable Sensors

Ohnishi,

Kosaka,

Hama

et al. 2024

Sensors

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Storytelling is one of the most important learning activities for children since reading aloud from a picture book stimulates children’s curiosity, emotional development, and imagination. For effective education, the procedures for storytelling activities need to be improved according to the children’s level of curiosity. However, young children are not able to complete questionnaires, making it difficult to analyze their level of interest. This paper proposes a method to estimate children’s curiosity in picture book reading activities at five levels by recognizing children’s behavior using acceleration and angular velocity sensors placed on their heads. We investigated the relationship between children’s behaviors and their levels of curiosity, listed all observed behaviors, and clarified the behavior for estimating curiosity. Furthermore, we conducted experiments using motion sensors to estimate these behaviors and confirmed that the accuracy of estimating curiosity from sensor data is approximately 72%.

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“…Fónagy és Magdics (1967) adatai szerint a többféle érzelmet kifejező beszédben előfordult érdes, rekedtes zönge. A glottalizációt az érzelmek automatikus felismerésében is használták (Batliner et al 2007).…”

Section: öSszegzés Következtetésekunclassified

A spontán beszéd a nem és az életkor függvényében gyermek- és fiatal felnőttkorban

Tóth¹

2017

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Associating children's non-verbal and verbal behaviour: Body movements, emotions, and laughter in a human-robot interaction

Cited by 13 publications

References 4 publications

Random Discriminative Projection Based Feature Selection with Application to Conflict Recognition

Random Discriminative Projection Based Feature Selection with Application to Conflict Recognition

A Curiosity Estimation in Storytelling with Picture Books for Children Using Wearable Sensors

A spontán beszéd a nem és az életkor függvényében gyermek- és fiatal felnőttkorban

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