A Novel Hybridized Strategy for Machine Translation of Indian Languages

  • A. Santhanavijayan
  • D. Naresh Kumar
  • Gerard Deepak
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1118)


Only a few translation systems exist for translations between an Aryan language and a Dravidian language, and moreover, the existing system does not perform quite efficiently. In this paper, the cognitive gap between two Indian languages namely Hindi and Malayalam is bridged. This paper proposes a Hindi to Malayalam machine translation system using hybridized strategies such as phrase-based translation, word alignment, and a language model with the emphasis on transition probability computation. Phrase-based translation breaks down a sentence into phrases and translates each phrase independently. This technique is applied on a Hindi–Malayalam parallel corpus. The proposed model interoperates between Hindi and Malayalam Languages. Although standard natural language computing techniques are encompassed, the arrangement of the techniques to suit a pair of Indian languages that are semantically incompliant and achieving a high accuracy is definitely a challenge and is achieved in this paper. The proposed hybridized approach outperforms all the other existing strategies and yields an average precision of 90.725% with a low word error rate of 9.125.


Language model Machine translation Phrase-based translation Word alignment 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • A. Santhanavijayan
    • 1
  • D. Naresh Kumar
    • 2
  • Gerard Deepak
    • 1
  1. 1.Department of Computer Science & EngineeringNational Institute of TechnologyTiruchirappalliIndia
  2. 2.Department of Mechanical EngineeringNational Institute of TechnologyTiruchirappalliIndia

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