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The terms extracted during the syntactic analysis are stored in the keyword table and are
used for selection of topics and words during the conversation synthesis.
Fig. 3. Examples of Generated Conversation
Note that in our current system, we use Japanese documents as the input. Because we are
using only syntactic information output by the Japanese parser, our mechanism is also
applicable to other languages such as English. We use a rather simple mechanism to
generate actual conversations in the system, which includes rules to select fragments
containing similar words and rules to change topics. The contents in the encyclopedia are
divided into seven categories, i.e. geography, history, politics, economy, society, culture and
life. When the topic in a conversation moves from one topic to another, the system generates
utterance showing such move. As for the speech synthesis part, we use the synthesizer
“Polluxstar” developed by Oki Electric Industry Co. Ltd., Japan. The two authors of this
paper, one male and one female, recorded 400 sentences each and the two characters in the
system talk to each other by impersonating our voices. The images of the two characters are
also based on the authors.
Because this system uses simple template-like knowledge, it cannot generate semantically
deep conversation on a topic by considering context or by compiling highly precise rules to
extract script-like information from text. Thus, the mechanism used in this system has room
for improvement to create conversations for knowledge transfer.
3. Efficiency of hearing a conversation comparing with hearing a monologue
In the daily transfer of knowledge, such as in a cooking program on TV, there are not only
the reading aloud of recipes by the presenter but also conversation between the cook and
assistant. Through such conversations, information which viewers want to know and which
they should memorize is transferred to them naturally.
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