Quantum Neural Network Based Machine Translator for Hindi to English

Joint Authors

Narayan, Ravi
Singh, V. P.
Chakraverty, Snehashish

Source

The Scientific World Journal

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-02-27

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

This paper presents the machine learning based machine translation system for Hindi to English, which learns the semantically correct corpus.

The quantum neural based pattern recognizer is used to recognize and learn the pattern of corpus, using the information of part of speech of individual word in the corpus, like a human.

The system performs the machine translation using its knowledge gained during the learning by inputting the pair of sentences of Devnagri-Hindi and English.

To analyze the effectiveness of the proposed approach, 2600 sentences have been evaluated during simulation and evaluation.

The accuracy achieved on BLEU score is 0.7502, on NIST score is 6.5773, on ROUGE-L score is 0.9233, and on METEOR score is 0.5456, which is significantly higher in comparison with Google Translation and Bing Translation for Hindi to English Machine Translation.

American Psychological Association (APA)

Narayan, Ravi& Singh, V. P.& Chakraverty, Snehashish. 2014. Quantum Neural Network Based Machine Translator for Hindi to English. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1049792

Modern Language Association (MLA)

Narayan, Ravi…[et al.]. Quantum Neural Network Based Machine Translator for Hindi to English. The Scientific World Journal No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1049792

American Medical Association (AMA)

Narayan, Ravi& Singh, V. P.& Chakraverty, Snehashish. Quantum Neural Network Based Machine Translator for Hindi to English. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1049792

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1049792