Abstract
This paper is concerned with dialogue state tracking (DST) in a task-oriented dialogue system. Building a DST module that is highly effective is still a challenging issue, although significant progresses have been made recently. This paper proposes a new approach to dialogue state tracking, referred to as Seq2Seq-DU, which formalizes DST as a sequence-to-sequence problem. Seq2Seq-DU employs two BERT-based encoders to respectively encode the utterances in the dialogue and the descriptions of schemas, an attender to calculate attentions between the utterance embeddings and the schema embeddings, and a decoder to generate pointers to represent the current state of dialogue. Seq2Seq-DU has the following advantages. It can jointly model intents, slots, and slot values; it can leverage the rich representations of utterances and schemas based on BERT; it can effectively deal with categorical and non-categorical slots, and unseen schemas. In addition, Seq2Seq-DU can also be used in the NLU (natural language understanding) module of a dialogue system. Experimental results on benchmark datasets in different settings (SGD, MultiWOZ2.2, MultiWOZ2.1, WOZ2.0, DSTC2, M2M, SNIPS, and ATIS) show that Seq2Seq-DU outperforms the existing methods.- Anthology ID:
- 2021.acl-long.135
- Volume:
- Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Editors:
- Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
- Venues:
- ACL | IJCNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1714–1725
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2021.acl-long.135/
- DOI:
- 10.18653/v1/2021.acl-long.135
- Cite (ACL):
- Yue Feng, Yang Wang, and Hang Li. 2021. A Sequence-to-Sequence Approach to Dialogue State Tracking. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1714–1725, Online. Association for Computational Linguistics.
- Cite (Informal):
- A Sequence-to-Sequence Approach to Dialogue State Tracking (Feng et al., ACL-IJCNLP 2021)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2021.acl-long.135.pdf
- Code
- sweetalyssum/Seq2Seq-DU
- Data
- Dialogue State Tracking Challenge, MultiWOZ, SGD, SNIPS, Wizard-of-Oz