A cooperative and conversational virtual agent for M-commerce applications

The aim of this paper is to present a cooperative approach to improve the Human-System spoken dialogues. The main advantage of the proposed approach is its ability to reach both of the user and the system goals more efficiently. The strategy that underlines our system is well adapted to the mobile applications since it involves effective spoken exchanges to reach the users' and system mutual goals. The proposed framework is built in order to use the Hidden Markov Models (HMMs) based CMUS-phinx speech recognition engine for mobile communications. To evaluate our approach a case-study in the M-trading field is considered. The analysis of the case study shows the efficiency of our strategy in comparison with the usual ones.