TY - GEN
T1 - Collection of example sentences for non-task-oriented dialog using a spoken dialog system and comparison with hand-crafted DB
AU - Kageyama, Yukiko
AU - Chiba, Yuya
AU - Nose, Takashi
AU - Ito, Akinori
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - Designing a question-answer database is important to make natural conversation for an example-based dialog system. We focused on the method to collect the example sentences by actual conversations with the system. In this study, examples in the database were collected from the conversation logs, then we investigated the relationship between the response accuracy and the number of the interaction. In the experiment, the transcriptions of the user’s utterances are added to the database at every end of the interaction. The responce sentences in the database were created manually. The result showed that the response accuracy appropriateness improved as increasing the number of the interactions and saturated at around 70%. In addition, we compared the collected database with the fully handcrafted database by the subjective evaluation. The score of the user satisfaction, dialog engagement, intelligence, and willingness to use were higher than the handcrafted database, and these results suggested that the proposed method can obtain more appropriate examples to the actual conversation from subjective point of view.
AB - Designing a question-answer database is important to make natural conversation for an example-based dialog system. We focused on the method to collect the example sentences by actual conversations with the system. In this study, examples in the database were collected from the conversation logs, then we investigated the relationship between the response accuracy and the number of the interaction. In the experiment, the transcriptions of the user’s utterances are added to the database at every end of the interaction. The responce sentences in the database were created manually. The result showed that the response accuracy appropriateness improved as increasing the number of the interactions and saturated at around 70%. In addition, we compared the collected database with the fully handcrafted database by the subjective evaluation. The score of the user satisfaction, dialog engagement, intelligence, and willingness to use were higher than the handcrafted database, and these results suggested that the proposed method can obtain more appropriate examples to the actual conversation from subjective point of view.
KW - Dialog collection
KW - Non-task-oriented dialog
KW - Spoken dialog system
UR - http://www.scopus.com/inward/record.url?scp=85024499760&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85024499760&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-58750-9_63
DO - 10.1007/978-3-319-58750-9_63
M3 - Conference contribution
AN - SCOPUS:85024499760
SN - 9783319587493
T3 - Communications in Computer and Information Science
SP - 458
EP - 464
BT - HCI International 2017 - Posters Extended Abstracts - 19th International Conference, HCI International 2017, Proceedings
A2 - Stephanidis, Constantine
PB - Springer Verlag
T2 - 19th International Conference on Human-Computer Interaction, HCI International 2017
Y2 - 9 July 2017 through 14 July 2017
ER -