Concurrent Acquisition of the Meaning of Sentence-Final Particles and Nouns Through Human-Robot Interaction
Sentence-final particles serve an important role in spoken Japanese, because they express the speaker’s mental attitudes toward a proposition and/or an interlocutor. They are acquired at early ages and occur very frequently in everyday conversation. However, there has been little proposal for a computational model of the acquisition of sentence-final particles. In this paper, we report on a study in which a robot learns how to react to utterances that have a sentence-final particle and gives appropriate responses based on rewards given by an interlocutor, and at the same time, learns the meaning of nouns. Preliminary experimental result shows that the robot learns to react correctly in response to yo, which expresses the speaker’s intention to communicate new information, and to ne, which denotes the speaker’s desire to confirm that some information is shared, and also learns the correct referents of nouns.
Keywordslanguage acquisition function words reinforcement learning
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- 1.Alishahi, A.: Computational Modeling of Human Language Acquisition, Morgan & Claypool (2010)Google Scholar
- 2.Kinsui, S.: Latest information on Linguistics: Japanese language study: Sentence-final particles yo and ne. Gengo 22(4), 118–121 (1993) (in Japanese )Google Scholar
- 3.Ogami, R., Matsuoka, H., Araki, O., Shibata, R., Takaoka, Y., Tsuchisaka, Y., Wu, X., Fukada, C., Ozeki, M., Oka, N.: Meaning acquisition of function words through human-robot interaction: Viewing the meaning of sentence-final particles as appropriate actions for utterances. Paper Presented at Human-Agent Interaction Symposium 2012, 2D-7 (2012) (in Japanese)Google Scholar
- 4.Ohshima, N., Ohyama, Y., Odahara, Y., De Silva, P.R.S., Okada, M.: Talking-ally: Intended persuasiveness by the utilizing hearership and addressivity. In: Proceedings of the Fourth International Conference on Social Robotics, pp. 317–326 (2012)Google Scholar
- 5.Oka, N., Ogami, R., Wu, X., Fukada, C., Ozeki, M.: Acquiring the meaning of sentence-final particles yo and ne through human-robot interaction. Paper Presented at the First International Conference on Human-Agent Interaction, Sapporo, Japan (2013)Google Scholar
- 6.Sutton, R.S., Barto, A.G.: Reinforcement learning: An introduction. MIT Press, Cambridge (1998)Google Scholar