English corpus translation system based on FPGA and machine learning

Abstract

ABSTRACT Corpus construction language is one of the essential parts of any language. A parallel English corpus translation language is a package that contains a collection of languages and their original translation materials. The corpus process translates text from one language to another by combining machine translation computation and language knowledge. In the machine translation, the text translation finds the corresponding source language with the help of language rules, which are simply the source language of the meaning of the words in the target language. Unfortunately, good sentences are mainly due in parallel because automatic translation in some languages does get less than enough progress. The primary problem is that this Indian language machine translation research does not play an important role. This translation process requires a person who is proficient in both languages and is a very time-consuming process. The Proposed algorithm Decision Bilingual Evaluation (DBE) predicting the English corpus machine translation using Field Programmable Gate Array (FPGA) and machine learning approach, an automated translation system developed. Work is to build a co-corpus of good quality and quantity in various fields, and the sentences from four languages (English- Tamil, English-Hindi, English-Malayalam, and English-Panjabi). The system encoder includes a network of encoders and decoders. The encoder uses input sentences to create a vector representation, and the decoder uses this vector and publishes words in the target language.