A Casual Conversation System Using Modality and Word Associations Retrieved from the Web

In this paper we present a textual dialogue system that uses word associations retrieved from the Web to create propositions. We also show experiment results for the role of modality generation. The proposed system automatically extracts sets of words related to a conversation topic set freely by a user. After the extraction process, it generates an utterance, adds a modality and verifies the semantic reliability of the proposed sentence. We evaluate word associations extracted form the Web, and the results of adding modality. Over 80% of the extracted word associations were evaluated as correct. Adding modality improved the system significantly for all evaluation criteria. We also show how our system can be used as a simple and expandable platform for almost any kind of experiment with human-computer textual conversation in Japanese. Two examples with affect analysis and humor generation are given.

• Type: Conference
• Year: 2008
• Where: EMNLP
• Authors: Shinsuke Higuchi, Rafal Rzepka, Kenji Araki
• Keywords: EMNLP 2008, Extracted Word Associations, Modality Generation, Natural Language Processing, Word Associations