TY - GEN
T1 - A simultaneous recognition framework for the spoken language understanding module of intelligent personal assistant software on smart phones
AU - Lee, Changsu
AU - Ko, Youngjoong
AU - Seo, Jungyun
N1 - Publisher Copyright:
© 2015 Association for Computational Linguistics.
PY - 2015
Y1 - 2015
N2 - The intelligent personal assistant software such as the Apple's Siri and Samsung's S-Voice has been issued these days. This paper introduces a novel Spoken Language Understanding (SLU) module to predict user's intention for determining system actions of the intelligent personal assistant software. The SLU module usually consists of several connected recognition tasks on a pipeline framework, whereas the proposed SLU module simultaneously recognizes four recognition tasks on a recognition framework using Conditional Random Fields (CRF). The four tasks include named entity, speech-act, target and operation recognition. In the experiments, the new simultaneous recognition method achieves the higher performance of 4% and faster speed of about 25% than other method using a pipeline framework. By a significance test, this improvement is considered to be statistically significant as a p-value of smaller than 0.05.
AB - The intelligent personal assistant software such as the Apple's Siri and Samsung's S-Voice has been issued these days. This paper introduces a novel Spoken Language Understanding (SLU) module to predict user's intention for determining system actions of the intelligent personal assistant software. The SLU module usually consists of several connected recognition tasks on a pipeline framework, whereas the proposed SLU module simultaneously recognizes four recognition tasks on a recognition framework using Conditional Random Fields (CRF). The four tasks include named entity, speech-act, target and operation recognition. In the experiments, the new simultaneous recognition method achieves the higher performance of 4% and faster speed of about 25% than other method using a pipeline framework. By a significance test, this improvement is considered to be statistically significant as a p-value of smaller than 0.05.
UR - https://www.scopus.com/pages/publications/84944071608
U2 - 10.3115/v1/p15-2134
DO - 10.3115/v1/p15-2134
M3 - Conference contribution
AN - SCOPUS:84944071608
T3 - ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference
SP - 818
EP - 822
BT - ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference
PB - Association for Computational Linguistics (ACL)
T2 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015
Y2 - 26 July 2015 through 31 July 2015
ER -