Implications of Multi-Word Expressions on English to Bharti Braille Machine Translation
This addresses translation quality for visually impaired users in India, but it is incremental as it builds on existing NMT methods.
The paper tackles improving English to Bharti Braille machine translation by adding a sub-module for multi-word expressions to a baseline NMT model, resulting in quality improvements ranging from 22.08% to 23.30% across five language pairs.
In this paper, we have shown the improvement of English to Bharti Braille machine translation system. We have shown how we can improve a baseline NMT model by adding some linguistic knowledge to it. This was done for five language pairs where English sentences were translated into five Indian languages and then subsequently to corresponding Bharti Braille. This has been demonstrated by adding a sub-module for translating multi-word expressions. The approach shows promising results as across language pairs, we could see improvement in the quality of NMT outputs. The least improvement was observed in English-Nepali language pair with 22.08% and the most improvement was observed in the English-Hindi language pair with 23.30%.