Abstract:In large societies like India there is a huge demand to convert one human language into another. Lots of work has been done in this area. Many transfer based MTS have developed for English to other languages, as MANTRA CDAC Pune, MATRA CDAC Pune, SHAKTI IISc Bangalore and IIIT Hyderabad. Still there is a little work done for Hindi to other languages. Currently we are working on it. In this paper we focus on designing a system, that translate the document from Hindi to English by using transfer based approach. This system takes an input text check its structure through parsing. Reordering rules are used to generate the text in target language. It is better than Corpus Based MTS because Corpus Based MTS require large amount of word aligned data for translation that is not available for many languages while Transfer Based MTS requires only knowledge of both the languages(source language and target language) to make transfer rules. We get correct translation for simple assertive sentences and almost correct for complex and compound sentences.
Abstract: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.
Abstract:Evaluation plays a crucial role in development of Machine translation systems. In order to judge the quality of an existing MT system i.e. if the translated output is of human translation quality or not, various automatic metrics exist. We here present the implementation results of different metrics when used on Hindi language along with their comparisons, illustrating how effective are these metrics on languages like Hindi (free word order language).