Mind Your Inflections! Improving NLP for Non-Standard Englishes with Base-Inflection Encoding

Samson Tan, Shafiq Joty, Lav Varshney, Min-Yen Kan


Abstract
Inflectional variation is a common feature of World Englishes such as Colloquial Singapore English and African American Vernacular English. Although comprehension by human readers is usually unimpaired by non-standard inflections, current NLP systems are not yet robust. We propose Base-Inflection Encoding (BITE), a method to tokenize English text by reducing inflected words to their base forms before reinjecting the grammatical information as special symbols. Fine-tuning pretrained NLP models for downstream tasks using our encoding defends against inflectional adversaries while maintaining performance on clean data. Models using BITE generalize better to dialects with non-standard inflections without explicit training and translation models converge faster when trained with BITE. Finally, we show that our encoding improves the vocabulary efficiency of popular data-driven subword tokenizers. Since there has been no prior work on quantitatively evaluating vocabulary efficiency, we propose metrics to do so.
Anthology ID:
2020.emnlp-main.455
Original:
2020.emnlp-main.455v1
Version 2:
2020.emnlp-main.455v2
Volume:
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Month:
November
Year:
2020
Address:
Online
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5647–5663
Language:
URL:
https://aclanthology.org/2020.emnlp-main.455
DOI:
10.18653/v1/2020.emnlp-main.455
Bibkey:
Cite (ACL):
Samson Tan, Shafiq Joty, Lav Varshney, and Min-Yen Kan. 2020. Mind Your Inflections! Improving NLP for Non-Standard Englishes with Base-Inflection Encoding. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 5647–5663, Online. Association for Computational Linguistics.
Cite (Informal):
Mind Your Inflections! Improving NLP for Non-Standard Englishes with Base-Inflection Encoding (Tan et al., EMNLP 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.emnlp-main.455.pdf
Video:
 https://slideslive.com/38938886
Code
 salesforce/bite
Data
BookCorpusMultiNLI