Input Utterance Complementation Method by Anaphora Resolution for Spontaneous Utterances on Spoken Dialog Systems

In this study, we propose a method for generating response utterances which take into account contexts and topics of the dialog by complementing omitted words such as subjects in the input utterances of dialog systems. In order to complement omitted words in the input utterances, an automatic anaphora resolution based on the centering theory is performed. To achieve highly accurate anaphora resolution, we also performed spoken-to-written style conversion based on sequence-to-sequence model using LSTM as a preprocessing. The results of evaluation experiments using NUCC, the Nagoya University Conversation Corpus showed that our proposed complementation method works robustly against errors in spoken-to-written style conversion.