Recognising the Social Attitude in Natural Interaction with Pedagogical Agents
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Transcript of Recognising the Social Attitude in Natural Interaction with Pedagogical Agents
Università degli studi di Bari “Aldo Moro”Dipartimento di Informatica
Recognising the Social Attitude in NaturalInteraction with Pedagogical Agents
B. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella{decarolis, ferilli, novielli}@di.uniba.it, {fabio.leuzzi, fulvio.rotella}@uniba.it
DIDAMATICA, Informatica per la DidatticaTaranto, Italy, May 14-16, 2012
Overview
● Introduction
● Objective
● The proposed model
● The proposed approach
● Signs of social attitude
● Evaluation
● Conclusions
● Future works
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 2
Introduction
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 3
Pedagogical Conversational Agent (PCA)
● fulfil pedagogical goals
● interact with the user through a natural dialog by
appropriately mixing verbal and non verbal expressions:
● recognize verbal and non-verbal inputs
● generate verbal and non-verbal outputs
● handle typical functions of human conversations,
with particular emphasis on social aspects
Objective
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 4
Aim: building a multimodal framework for the recognition
of the social response of users to a PCA.
In particular: building a framework that integrates the
analysis of the linguistic component of the user's
communicative act with the analysis of the acoustic
features of the spoken sentence and of the gestures.
ObjectiveThe intuition
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 5
The combination of these different input modalities may
improve the recognition of multimodal behaviours that
may denote the openness attitude of the users towards
the embodied agent.
Steps:
● Recognize signs of social attitude
● Build a model to infer the user attitude toward the PCA
● Adapt the dialog strategies accordingly
The proposed model
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 6
Dynamic Belief Network (DBN):
● handling uncertainty and incompleteness of data
● representing situations which gradually evolve from a
dialog step to the next one
The proposed approach
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 7
● The model is initialized
● At every dialog step:
● Knowledge about the evidence is produced
● The produced knowledge is entered and propagated in the
network
● The model revises the probabilities of the social attitude node
● The new probabilities of the signs of social attitude are used
for planning the next agent move
● The probability of the social attitude node supports revising
high-level planning of the agent behaviour
Signs of social attitudein the language
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 8
● Sense of intimacy (use of common jargon)
● Friendly self-introduction
● Familiar style
● Attempt to establish a common ground
● Talk about self
● Personal questions about the agent
● Irony and humour
● Benevolent/polemic attitude towards the system failures
● Favourable/negative comments
● Interest to protract interaction
● Friendly farewell
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 9
Praat functions to extract features related to:
● variation of the fundamental frequency
● variation of energy
● variation of harmonicity
● Spectrum Central Moment, Standard Deviation, Gravity
centre, Skeweness and Kurtosis
● speech rate
Classification (using NNge algorithm) of user's spoken
sentence into 3 classes: positive, negative and neutral.
Signs of social attitudein the prosody
Signs of social attitudein the gestures
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 10
Gesture recognition performed using
Microsoft Kinect + KinectDTW
need to consider only a subset of gestures compatible
with the nodes in
the skeleton that
the Kinect SDK
can detect.
Signs of social attitudein the gestures
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 11
Signal Possible meaning(s)
Crossed arms Defensiveness, closure
Gripping own upper arms
Insecurity, closure
Adjusting cuff, watchstrap, tic, using
an arm across the body
Nervouseness, negative attitude
touching or scratching shoulder using arm
across body
Nervouseness, negative attitude
EvaluationCollecting a corpus
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 12
We collected moltimodal dialog moves, consisting in
linguistic, acoustic and gesture data.
Participants: 2 groups of 5 italian students aged between
16 and 25 (equally distributed by gender).
Goal: getting information about a correct diet in order to
stay in shape.
PCA role: nutrition expert.
Collected: about 300 moves.
EvaluationCollecting a corpus
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 13
EvaluationResults
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 14
Move U6 Move U7
Move U8
Conclusions
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 15
Existing model for recognising social attitude enriched
with the analysis of signals regarding non-verbal
communication: prosody and gesture.
We propose an extension of the multimodal analysis to
gesture modeling, according to the meanings that
psycholinguistic researchers attach to gestures in
conversations.
Preliminary experiments show promising results.
Future works
Recognising the Social Attitude in Natural Interaction with Pedagogical AgentsB. De Carolis, S. Ferilli, N. Novielli, F. Leuzzi, F. Rotella 16
● Improving gesture recognition since the new Kinect
should allow for a better hand recognition
● extending the social attitude analysis with facial
expressions
Carrying out more evaluation studies in order to test the
robustness of our framework:
● for social attitude recognition in different scenarios
● with respect to different interaction modalities with both
ECAs and Robots