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MTee: Open Machine Translation Platform for Estonian Government
We present the MTee project - a research initiative funded via an Estonian public procurement to develop machine translation technology that is open-source and free of charge.
Teaching Llama a New Language Through Cross-Lingual Knowledge Transfer
This paper explores cost-efficient methods to adapt pretrained Large Language Models (LLMs) to new lower-resource languages, with a specific focus on Estonian.
To Err Is Human, but Llamas Can Learn It Too
This study explores enhancing grammatical error correction (GEC) through artificial error generation (AEG) using language models (LMs).
Autocorrect for Estonian texts: final report from project EKTB25
To mitigate this, (1) we annotated more correction data for model training and testing, (2) we tested transfer-learning, i. e. retraining machine learning models created for other tasks, so as not to depend solely on correction data, (3) we compared the developed method and model with alternatives, including large language models.
Grammatical Error Correction and Style Transfer via Zero-shot Monolingual Translation
Both grammatical error correction and text style transfer can be viewed as monolingual sequence-to-sequence transformation tasks, but the scarcity of directly annotated data for either task makes them unfeasible for most languages.
