Recognition of Paralinguistic Information in Spoken Dialogue Systems for Elderly People.

Different strategies are currently studied and applied with the objective to facilitate the acceptability and effective use of Ambient Assisted Living (AAL) applications. One of these strategies is the development of speech-based interfaces to facilitate the communication between the system and the user. In addition to the improvement of communication, the voice of the elder can be also used to automatically classify some paralinguistic phenomena associated with specific mental states and assess the quality of the interaction between the system and the target user. This paper presents our initial work in the construction of these classifiers using an existent spoken dialogue corpus. We present the performance obtained in our models using spoken dialogues from young and older users. We also discuss the further work to effectively integrate these models into AAL applications.