Zero-Shot Cross-Lingual Sequence Tagging as Seq2Seq Generation for Joint Intent Classification and Slot Filling
Fei Wang, Kuan-hao Huang, Anoop Kumar, Aram Galstyan, Greg Ver steeg, Kai-wei Chang
Abstract
The joint intent classification and slot filling task seeks to detect the intent of an utterance and extract its semantic concepts. In the zero-shot cross-lingual setting, a model is trained on a source language and then transferred to other target languages through multi-lingual representations without additional training data. While prior studies show that pre-trained multilingual sequence-to-sequence (Seq2Seq) models can facilitate zero-shot transfer, there is little understanding on how to design the output template for the joint prediction tasks. In this paper, we examine three aspects of the output template – (1) label mapping, (2) task dependency, and (3) word order. Experiments on the MASSIVE dataset consisting of 51 languages show that our output template significantly improves the performance of pre-trained cross-lingual language models.- Anthology ID:
- 2022.mmnlu-1.6
- Volume:
- Proceedings of the Massively Multilingual Natural Language Understanding Workshop (MMNLU-22)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Venue:
- MMNLU
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 53–61
- Language:
- URL:
- https://aclanthology.org/2022.mmnlu-1.6
- DOI:
- Cite (ACL):
- Fei Wang, Kuan-hao Huang, Anoop Kumar, Aram Galstyan, Greg Ver steeg, and Kai-wei Chang. 2022. Zero-Shot Cross-Lingual Sequence Tagging as Seq2Seq Generation for Joint Intent Classification and Slot Filling. In Proceedings of the Massively Multilingual Natural Language Understanding Workshop (MMNLU-22), pages 53–61, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Zero-Shot Cross-Lingual Sequence Tagging as Seq2Seq Generation for Joint Intent Classification and Slot Filling (Wang et al., MMNLU 2022)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2022.mmnlu-1.6.pdf