The effects of listening agent in speech-based on-line test system

Speech-based test is a one of the best ways to train students' level of proficiency. However, in e-learning it is difficult for students to maintain their concentration when speaking to a monitor. We propose speech-based online test system employing a human-likely embodied graphical agent as a listener. The developed system consists of three modules, user recognition, agent's non-verbal behavior realization, and learning controller. The system is developed with HTML5, Javascript, and WebGL, so that it should be compatible with any modern Web-browsers. To investigate the effects of the use of the listener agent in speech-based test on learning efficacy and naturalness of speech, we will conduct a one-way between-subject design experiment with three groups. In experimental group, participants speech to a listening agent with listener behavior depicted on a monitor during a speech-based test. On the other hand, in first control group, participants take the test with the listening agent but the agent does not move while the participants' speech. In second control group, participants take the test without the listening agent. Then, the result of listening scores will be statistically tested.