Sentence Wise Telugu to English Translation of Vemana Sathakam using LSTM
P.Sujatha1, D. Lalitha Bhaskari2
1P. Sujatha, research scholar, Department of Computer Science and Systems Engineering, Andhra university college of engineering (A), Andhra university.
2D. Lalitha Bhaskari, Professor, Department of Computer Science and Systems Engineering, Andhra university college of engineering (A), Andhra university.
Manuscript received on November 11, 2019. | Revised Manuscript received on November 20 2019. | Manuscript published on 30 November, 2019. | PP: 10739-10743 | Volume-8 Issue-4, November 2019. | Retrieval Number: D4340118419/2019©BEIESP | DOI: 10.35940/ijrte.D4340.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Language translation is a power of humans where machines are lagging and need to acquire. Previous statistical machine translation is used for translation but is applicable for large and similar grammar structure dataset. In this paper neural machine translation with long short term memory (LSTM) is used for addressing the issue. This paper uses a bidirectional LSTM to translate Telugu literary poems of Yogi Vemana to English which exhibited satisfactory translation. The results are compared with existing and proposed methods. NMT with LSTM yields better in language translation.
Keywords: Machine Translation, Neural Machine Translation, Long Short Term Memory.
Scope of the Article: Natural Language Processing and Machine Translation.