Assessing the Quality of MT Systems for Hindi to English Translation
This work addresses the need for efficient translation quality assessment for Hindi-English systems, but it is incremental as it applies existing methods to a specific language pair.
This paper tackled the problem of evaluating machine translation quality for Hindi to English by comparing different MT engines using automatic metrics like BLEU and METEOR, and found that the results were compared with human rankings to assess accuracy.
Evaluation plays a vital role in checking the quality of MT output. It is done either manually or automatically. Manual evaluation is very time consuming and subjective, hence use of automatic metrics is done most of the times. This paper evaluates the translation quality of different MT Engines for Hindi-English (Hindi data is provided as input and English is obtained as output) using various automatic metrics like BLEU, METEOR etc. Further the comparison automatic evaluation results with Human ranking have also been given.