Bridging Worlds
The Neural Machine Translation for Native Peruvian Languages project was born from a deeply personal mission. It was initiated by member of AiMara Lab, both systems and computer engineers deeply rooted in the Aymara culture, whose native language is Aymara. Their vision was to build a bridge between their ancestral heritage and the forefront of technological evolution.
What began as a personal initiative has since grown into a collaborative movement, attracting more individuals passionate about a shared goal: translating the Aymara language for a global audience. Our mission is twofold: to ensure the Aymara community is an active participant in the digital age, and to develop practical solutions that directly benefit native communities.
Our Technology
Our progress is built on a solid foundation of cutting-edge research. The current translator prototype was developed using principles from the seminal papers that power modern AI:
- ● "Attention is All you Need" - Vaswani, et al. (2017)
- ● "Effective Approaches to Attention-based Neural Machine Translation" - Luong, et al. (2015)
This approach has yielded promising results, validated by standard industry metrics such as BLEU, ROUGE, and METEOR.
Try the Translator PrototypeSITA Platform
To power our models, we developed a comprehensive system for corpus creation and validation, named SITA. It allows us to upload sentences in Spanish, which are then translated and recorded by registered native speakers.
Explore SITAPeruvian Data Initiative
A robust translation model requires a vast and diverse dataset. AiMara Lab is actively recovering and structuring data from various Peruvian contexts, including news, health, education, and legal sectors.
View Data Initiative ProgressRelated Publications
● Modelos neuronales de traducción automática para la lengua nativa aimara
Apaza Alanoca, Honorio (2025). Master's Thesis. Universidad Nacional de San Agustín.
Access Thesis● Neural Machine Translation for Aymara to Spanish
Alanoca, H. A., et al. (2023). In Intelligent Systems and Applications (pp. 290–298). Springer International Publishing.
View Paper● Neural Machine Translation for Native Language Aymara to English
Apaza, H., et al. (2023). In Proceedings of the Future Technologies Conference (FTC) 2022 (pp. 565–576). Springer International Publishing.
View PaperBuilding the Future
This project is more than just code; it's a commitment to cultural preservation and digital inclusion. We are continuously working to improve our models, expand our datasets, and build new tools for the Aymara community and the world.