*8.4. Pros and Cons of Our System*

We found several pros and cons of the twin-robot dialogue system through the field trial.

• Leading a dialogue by a robot

**Pros**. Participants who have no topic to discuss might have easily taken part in a dialogue. In general, it is quite challenging for people to initiate a dialogue unless they have topics they would want to talk about. We found that many participants had no topic to discuss with the robot. By the robot initiating a dialogue, those participants could have participated in the dialogue without worrying about initiating it.

**Cons**. Dialogue initiation by the robot may have frustrated some participants in case they had something they would have preferred to talk about with the robot.

• Patterning a dialogue

**Pros**. Participants who are not good at communicating smoothly might have easily followed a dialogue because the user could have predicted the flow of the dialogue. This aspect should be important in dialogues for elderly people with declining cognitive ability.

**Cons**. Participants who have no communication problems might have felt bored earlier during a dialogue if the dialogue was monotonous.

• Choosing robot responses by using keyword match of user answers

**Pros**. This method was clearly robust against speech recognition failures. In our question–answer–response dialogue model, if the speech recognition result contains words of the keyword attribute, the backchannel (comment) associated with the keyword is selected. Otherwise, the backchannel (comment) associated with no keyword (i.e., the default backchannel (comment)) is selected. Therefore, when the speech recognition result is a broken sentence, the default backchannel (comment) is selected in most cases. Because the default backchannel (comment) is a sentence that is coherent for any answer, the dialogue was usually coherent even if the speech recognition fails.

**Cons**. There are two situations for a dialogue to break down. First, there is the case where a user asks a robot a question while the robot is in the "answer mode". Here, the sentence associated with the default attribute is selected unless it was time for the user to be posing a question to the robot. Because the sentence of the default attribute is not meaningful to the

question, the dialogue would become unnatural. Second, there is the case where a keyword is matched owing to speech recognition failures, although this will rarely happen. For example, let us consider the following situation: a robot asks "Which countries do you want to travel, France or England?". Although a user answers France, the speech recognition result could be England. At this point, the dialogue would be strange because the robot would choose "England" as the response. To avoid this, we need more sophisticated algorithms.
