In this
paper we will propose the use of social robots as interface between users and
services in a Smart Environment. We will focus on the need for robots to recognize
the user’s feedback, in order to respond and revise its behaviour according to
user’s needs. As we believe speech is a natural and immediate input channel in
human-robot interaction, we will discuss the importance of recognising, besides
the linguistic content of the spoken sentence, the attitude of the user towards
the robot and the environment. In this way, the meaning of the user dialog will
be made clear when hardly recognisable by the analysis of the utterance
structure. Then, we will present the results of the application of a potential
approach used for integrating the linguistic analysis with the recognition of
the valence and arousal of the user’s utterance. In order to achieve this goal,
we collected and analysed a corpus of data to build an interpretation model
based on a Bayesian network. Then we tested the accuracy of the model using a
test dataset. Results will show that the integration of the linguistic content
with the recognition of some acoustic features of spoken sentences perform
better in recognising the key aspects of user’s feedback.