Masked Hard Coverage Mechanism on Pointer-generator Network for Natural Language Generation

Ting Hu, Christoph Meinel

2021

Abstract

Natural Language Generation (NLG) task is to generate natural language utterances from structured data. Seq2seq-based systems show great potentiality and have been widely explored for NLG. While they achieve good generation performance, over-generation and under-generation issues still arise in the generated results. We propose maintaining a masked hard coverage mechanism in the pointer-generator network, a seq2seq-based architecture that trains a switch policy to produce output sequences by partially copying from input structured data. The proposed mechanism can be regarded as the inner controlling module to keep track of the copying history and force the network to generate sentences accurately covering all information provided in structured data. Experimental results show that our coverage mechanism alleviates the over-generation and under-generation issues and achieves decent performance on the E2E NLG dataset.

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Paper Citation


in Harvard Style

Hu T. and Meinel C. (2021). Masked Hard Coverage Mechanism on Pointer-generator Network for Natural Language Generation.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 1177-1183. DOI: 10.5220/0010341211771183


in Bibtex Style

@conference{icaart21,
author={Ting Hu and Christoph Meinel},
title={Masked Hard Coverage Mechanism on Pointer-generator Network for Natural Language Generation},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={1177-1183},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010341211771183},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Masked Hard Coverage Mechanism on Pointer-generator Network for Natural Language Generation
SN - 978-989-758-484-8
AU - Hu T.
AU - Meinel C.
PY - 2021
SP - 1177
EP - 1183
DO - 10.5220/0010341211771183