# A Case Against Implicit Standards: Homophone Normalization in Machine Translation for Languages that use the Ge'ez Script

arXiv: https://arxiv.org/abs/2507.15142 · HTML: https://mlsanity.com/paper/2507.15142/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 41 references that are in the map.
- First posted on arXiv 20 Jul 2025.

## Builds on (most cited first, 16 of 16)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [A Call for Clarity in Reporting BLEU Scores](https://mlsanity.com/paper/1804.08771/) (2018)
- [No Language Left Behind: Scaling Human-Centered Machine Translation](https://mlsanity.com/paper/2207.04672/) (2022)
- [The State and Fate of Linguistic Diversity and Inclusion in the NLP World](https://mlsanity.com/paper/2004.09095/) (2020)
- [Beyond English-Centric Multilingual Machine Translation](https://mlsanity.com/paper/2010.11125/) (2020)
- [Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models](https://mlsanity.com/paper/2305.13707/) (2023)
- [Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation](https://mlsanity.com/paper/2412.03304/) (2024)
- [Towards Afrocentric NLP for African Languages: Where We Are and Where We Can Go](https://mlsanity.com/paper/2203.08351/) (2022)
- [KINNEWS and KIRNEWS: Benchmarking Cross-Lingual Text Classification for Kinyarwanda and Kirundi](https://mlsanity.com/paper/2010.12174/) (2020)
- [Adapting Multilingual LLMs to Low-Resource Languages using Continued Pre-training and Synthetic Corpus](https://mlsanity.com/paper/2410.14815/) (2024)
- [Low Resource Neural Machine Translation: A Benchmark for Five African Languages](https://mlsanity.com/paper/2003.14402/) (2020)
- [Introducing various Semantic Models for Amharic: Experimentation and Evaluation with multiple Tasks and Datasets](https://mlsanity.com/paper/2011.01154/) (2020)
- [Designing for Harm Reduction: Communication Repair for Multicultural Users' Voice Interactions](https://mlsanity.com/paper/2403.00265/) (2024)
- [Letters From the Past: Modeling Historical Sound Change Through Diachronic Character Embeddings](https://mlsanity.com/paper/2205.08256/) (2022)
- [The African Stopwords project: curating stopwords for African languages](https://mlsanity.com/paper/2304.12155/) (2023)

## Built on by (most cited first, 1 of 1)

- [Ethio-ASR: Joint Multilingual Speech Recognition and Language Identification for Ethiopian Languages](https://mlsanity.com/paper/2603.23654/) (2026)

## Abstract (arXiv)

Homophone normalization, where characters that have the same sound in a writing script are mapped to one character, is a pre-processing step applied in Amharic Natural Language Processing (NLP) literature. While this may improve performance reported by automatic metrics, it also results in models that are not able to understand different forms of writing in a single language. Further, there might be impacts in transfer learning, where models trained on normalized data do not generalize well to other languages. In this paper, we experiment with monolingual training and cross-lingual transfer to understand the impacts of normalization on languages that use the Ge'ez script. We then propose a post-inference intervention in which normalization is applied to model predictions instead of training data. With our simple scheme of post-inference normalization, we show that we can achieve an increase in BLEU score of up to 1.03 while preserving language features in training. Our work contributes to the broader discussion on technology-facilitated language change and calls for more language-aware interventions.