Aditi Kalyani

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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(More)
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,(More)
Despite the linguistic diversity, communication is important for economic and social growth. But it is impossible for a human being to know all languages. This led to the inception of machine translation. Machine Translation (MT) is a field of Artificial Intelligence and Natural Language Processing which deals with translation from one language to another(More)
Cloud computing model provides cloud computing resources as a RaaS. Turnaround time and cost is mainly concerned with this model. Amazon offers spot instances with less expense. Resource unavailability leads to ongoing execution interruption, thereby reducing the performance. EAIC model handles spot instance revocation to reduce cost and turnaround time. No(More)
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