As a low-resource language, Burmese is a language that’s native to Myanmar and elements of Bangladesh, India, China, and Thailand. There are round 33 million individuals who converse it’s a native language and round 10 million converse it as a second language. It comes from the Sino-Tibetan, Lolo-Burmese language household.
With regards to translating Burmese, this could be a very difficult activity for linguists, translators, and localization specialists as a result of it kinds part of the low-resource languages for NLP (Pure Language Processing). This will pose important obstacles in translation processes and with this in thoughts, we determined to share a few of our experiences working with Burmese as a low-resource language. Check out our shared findings beneath.
What’s a low-resource language?
In brief, a low-resource language is a language that faces challenges in translations and localization processes as a result of there may be not sufficient information to enter into an NLP system to get extra correct translations at a better proportion of the time a translation must be finished. NLP is a system of translation that gathers as a lot information as attainable for a supply language after which makes use of this information to translate the supply language right into a goal language. Nonetheless, when there may be too little information on a low-resource language, what typically finally ends up occurring is poor-quality translations with many errors that a man-made intelligence (AI) program coping with translation typically can’t choose up on.
That is why experience from human translators is so essential on this course of because the NLP for low-resource languages typically lacks a big sufficient information set to course of correct translations. Examples of high-resource languages are French, English, and Chinese language, whereas Burmese is a low-resource language as a result of there may be not a lot information to help high quality translations.
Why is Burmese thought-about a low-resource language?
Burmese is taken into account a low-resource language as a result of there has not been enough effort put into constructing a powerful NLP for low-resource languages. These languages are spoken by fewer individuals, there may be much less demand for these translations, and as such, AI and NLP databases do not need enough details about the language to course of and produce correct translations. That is why many errors crop up within the means of translating from and to Burmese.
1-StopAsia’s course of for fixing low-resource language points for Burmese
At 1-StopAsia, we’ve got first-hand expertise with translating Burmese. Nonetheless, on the outset, we observed a few errors that had cropped up within the means of translating this language. It was not solely that Burmese is likely one of the low-resource languages for NLP but in addition that this case led to a less-than-optimal answer for a number of of our shoppers.
As a result of high quality assurance is vital to our promise to our shoppers, we launched into a technique to resolve this challenge. Two of the commonest points that we recognized in Burmese translations have been spelling errors and mistranslations by the linguists.
To handle this challenge, we undertook a number of essential qualitative steps and created motion plans to make sure that the translations have been of top quality. For instance, relating to the misspelled phrases, we created glossaries that have been accepted by the shoppers that we might construct into our database of low-resource NLP for Burmese.
We additionally ensured that any mistranslations have been despatched again to the related linguists and we additionally expanded our expertise pool of linguists for Burmese in order that we might have higher-quality translation output going ahead.
Finally, this resolved the shopper’s points and we ended up with a positive answer for future initiatives that contain Burmese translation by guaranteeing that our current low-resource NLP was boosted each on the AI aspect via glossaries and pre-defined phrases and on the human aspect, however increasing and strengthening the standard of our Burmese translation group.
A continued dedication to high quality assurance for Burmese language translations
To make sure that we constantly ship high-quality translations in Burmese to every of our shoppers, we take essential and important steps to establish translation points as and once they come up and to develop motion plans to make sure that points are usually not repeated sooner or later. We additionally attempt to construct onto our NLP database for Burmese in order that it transforms from a low-resource to a high-resource language information set. This ensures continued high quality assurance from our group as we consider each the technological and human components of Burmese translations to provide each shopper needing such a translation the very best high quality output that they will anticipate.