TY - GEN
T1 - Automatic template feature extraction and the application to utterance in a dialogue system
AU - Mikami, Yoshitaka
AU - Hagiwara, Masafumi
N1 - Publisher Copyright:
© Association for Computing Machinery. All rights reserved.
PY - 2018/2/2
Y1 - 2018/2/2
N2 - In this paper, we propose an automatic template features extraction method and apply it to utterance generation in a dialogue system. Template-based utterance generation has been widely used in many dialogue systems because of its robustness. Although variety of templates and the appropriate selection are crucial points in the method, they have not been paid attention so far. This paper focuses on the points; first, we propose the new neural network model utilizingLSTM (Long Short-Term Memory) to extract effective and unique features for templates, and then applied it to utterance generation in a dialogue system. To examine the effectiveness of the proposed method, we conduct two kinds of experiments; subjective evaluation and dialogue breakdown detection experiment. In both of the experiments, the proposed method has shown higher accuracy than the conventional methods.
AB - In this paper, we propose an automatic template features extraction method and apply it to utterance generation in a dialogue system. Template-based utterance generation has been widely used in many dialogue systems because of its robustness. Although variety of templates and the appropriate selection are crucial points in the method, they have not been paid attention so far. This paper focuses on the points; first, we propose the new neural network model utilizingLSTM (Long Short-Term Memory) to extract effective and unique features for templates, and then applied it to utterance generation in a dialogue system. To examine the effectiveness of the proposed method, we conduct two kinds of experiments; subjective evaluation and dialogue breakdown detection experiment. In both of the experiments, the proposed method has shown higher accuracy than the conventional methods.
KW - Long short-term memory
KW - Sentence embeddings
KW - Template based dialogue system
KW - Utterance generation
UR - http://www.scopus.com/inward/record.url?scp=85060501275&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060501275&partnerID=8YFLogxK
U2 - 10.1145/3184066.3184069
DO - 10.1145/3184066.3184069
M3 - Conference contribution
AN - SCOPUS:85060501275
T3 - ACM International Conference Proceeding Series
SP - 164
EP - 168
BT - 2nd International Conference on Machine Learning and Soft Computing, ICMLSC 2018
PB - Association for Computing Machinery
T2 - 2nd International Conference on Machine Learning and Soft Computing, ICMLSC 2018
Y2 - 2 February 2018 through 4 February 2018
ER -