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 language | English |
|---|---|
| Title of host publication | Findings of the Association for Computational Linguistics |
| Subtitle of host publication | EMNLP 2023 |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 11578-11588 |
| Number of pages | 11 |
| ISBN (Electronic) | 9798891760615 |
| DOIs | |
| State | Published - 2023 |
| Event | 2023 Findings of the Association for Computational Linguistics: EMNLP 2023 - Hybrid, Singapore Duration: 6 Dec 2023 → 10 Dec 2023 |
Publication series
| Name | Findings of the Association for Computational Linguistics: EMNLP 2023 |
|---|
Conference
| Conference | 2023 Findings of the Association for Computational Linguistics: EMNLP 2023 |
|---|---|
| Country/Territory | Singapore |
| City | Hybrid |
| Period | 6/12/23 → 10/12/23 |
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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