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Consonant is all you need: a compact representation of English text for efficient NLP

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In natural language processing (NLP), the representation of text plays a crucial role in various tasks such as language modeling, sentiment analysis, and machine translation. The standard approach is to represent text in the same way as we, as humans, read and write. In this paper, we propose a novel approach to represent text with only consonants which presents a compact representation of English text that offers improved efficiency without sacrificing performance. We exploit the fact that consonants are more discriminative than vowels and by representing text using consonants, we can significantly reduce the overall memory and compute footprint required for storing and processing textual data.

Original languageEnglish
Title of host publicationFindings of the Association for Computational Linguistics
Subtitle of host publicationEMNLP 2023
PublisherAssociation for Computational Linguistics (ACL)
Pages11578-11588
Number of pages11
ISBN (Electronic)9798891760615
DOIs
StatePublished - 2023
Event2023 Findings of the Association for Computational Linguistics: EMNLP 2023 - Hybrid, Singapore
Duration: 6 Dec 202310 Dec 2023

Publication series

NameFindings of the Association for Computational Linguistics: EMNLP 2023

Conference

Conference2023 Findings of the Association for Computational Linguistics: EMNLP 2023
Country/TerritorySingapore
CityHybrid
Period6/12/2310/12/23

Bibliographical note

Publisher Copyright:
© 2023 Association for Computational Linguistics.

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems
  • Language and Linguistics
  • Linguistics and Language

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