Abstract
In this paper, we propose a chat response generation system using distributed expression of words by Word2vec. With the conventional one-hot representation method, there was a problem in that the model becomes complicated as the vocabulary increases, and only the words that appear in the dialogue corpus can be handled. We address these problems by using Word2vec and extend it to handle unknown words that did not appear in the conversation corpus. In a subjective evaluation experiment, we showed that various responses can be generated by estimating words using semantic prediction.
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References
Doddington G (2002) Automatic evaluation of machine translation quality using n-gram co-occurrence statistics. In: Proceedings of the Second International Conference on HLT ’02, pp 138–145
Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. arXiv:1412.6980
Kudo T (2005) Mecab: yet another part-of-speech and morphological analyzer. http://mecab.sourceforge.net/
Mikolov T, Chen K, Corrado G, Dean J (2013) Efficient estimation of word representations in vector space. arXiv:1301.3781
Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J (2013) Distributed representations of words and phrases and their compositionality. In: Proceedings of NIPS, pp 3111–3119
Mikolov T, Yih WT, Zweig G (2013) Linguistic regularities in continuous space word representations. In: Proceedings of NAACL-HLT 2013, pp 746–751
Shang L, Lu Z, Li H (2015) Neural responding machine for short-text conversation. Proceedings of ACL 2015, pp 1577–1586
Vinyals O, Le Q (2015) A neural conversational model. In: ICML Deep Learning Workshop
Wiseman S, Rush AM (2016) Sequence-to-sequence learning as beam-search optimization. Proceedings of EMNLP, pp 1296–1306
Yu L, Zhang W, Wang J, Yu Y (2016) SeqGAN: sequence generative adversarial nets with policy gradient. arXiv:1609.05473
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Furumai, K., Takiguchi, T., Ariki, Y. (2019). Chat Response Generation Based on Semantic Prediction Using Distributed Representations of Words. In: D'Haro, L., Banchs, R., Li, H. (eds) 9th International Workshop on Spoken Dialogue System Technology. Lecture Notes in Electrical Engineering, vol 579. Springer, Singapore. https://doi.org/10.1007/978-981-13-9443-0_26
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DOI: https://doi.org/10.1007/978-981-13-9443-0_26
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