Tigrinya Number Verbalization: Rules, Algorithm, and Implementation
Fitsum Gaim, Issayas Tesfamariam
TL;DR
This work addresses the lack of formalized rules for Tigrinya number verbalization, a bottleneck for Tigrinya NLP in TTS, ASR, and accessibility. It delivers a canonical rule set, a formal number-to-word algorithm, and an open-source Python implementation. The authors evaluate frontier LLMs to reveal substantial gaps in accurate Tigrinya numeral verbalization, motivating deterministic resources. The result is a robust foundation for Tigrinya NLP pipelines, language preservation, and accessible technology for speakers in low-resource settings.
Abstract
We present a systematic formalization of Tigrinya cardinal and ordinal number verbalization, addressing a gap in computational resources for the language. This work documents the canonical rules governing the expression of numerical values in spoken Tigrinya, including the conjunction system, scale words, and special cases for dates, times, and currency. We provide a formal algorithm for number-to-word conversion and release an open-source implementation. Evaluation of frontier large language models (LLMs) reveals significant gaps in their ability to accurately verbalize Tigrinya numbers, underscoring the need for explicit rule documentation. This work serves language modeling, speech synthesis, and accessibility applications targeting Tigrinya-speaking communities.