# Bilingual Word Level Language Identification for Omotic Languages

arXiv: https://arxiv.org/abs/2509.07998 · HTML: https://mlsanity.com/paper/2509.07998/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 44 references that are in the map.
- First posted on arXiv 5 Sep 2025.

## Builds on (most cited first, 10 of 10)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction](https://mlsanity.com/paper/2409.00265/) (2024)
- [Semantic-Driven Topic Modeling Using Transformer-Based Embeddings and Clustering Algorithms](https://mlsanity.com/paper/2410.00134/) (2024)
- [Ethio-Fake: Cutting-Edge Approaches to Combat Fake News in Under-Resourced Languages Using Explainable AI](https://mlsanity.com/paper/2410.02609/) (2024)
- [SMART-Vision: Survey of Modern Action Recognition Techniques in Vision](https://mlsanity.com/paper/2501.13066/) (2025)
- [First Attempt at Building Parallel Corpora for Machine Translation of Northeast India's Very Low-Resource Languages](https://mlsanity.com/paper/2312.04764/) (2023)
- [Evaluating the Effectiveness of XAI Techniques for Encoder-Based Language Models](https://mlsanity.com/paper/2501.15374/) (2025)
- [A Unified Framework with Novel Metrics for Evaluating the Effectiveness of XAI Techniques in LLMs](https://mlsanity.com/paper/2503.05050/) (2025)
- [Explainability in Neural Networks for Natural Language Processing Tasks](https://mlsanity.com/paper/2412.18036/) (2024)
- [Explainable AI: XAI-Guided Context-Aware Data Augmentation](https://mlsanity.com/paper/2506.03484/) (2025)

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

- [Multiclass Sentiment Analysis for Identifying Political Viewpoints](https://mlsanity.com/paper/2608.11049/) (2026)

## Abstract (arXiv)

Language identification is the task of determining the languages for a given text. In many real world scenarios, text may contain more than one language, particularly in multilingual communities. Bilingual Language Identification (BLID) is the task of identifying and distinguishing between two languages in a given text. This paper presents BLID for languages spoken in the southern part of Ethiopia, namely Wolaita and Gofa. The presence of words similarities and differences between the two languages makes the language identification task challenging. To overcome this challenge, we employed various experiments on various approaches. Then, the combination of the BERT based pretrained language model and LSTM approach performed better, with an F1 score of 0.72 on the test set. As a result, the work will be effective in tackling unwanted social media issues and providing a foundation for further research in this area.