CLAug 26, 2017

Machine Translation in Indian Languages: Challenges and Resolution

arXiv:1708.07950v32 citations
Originality Synthesis-oriented
AI Analysis

This addresses translation problems for Indian language speakers, but it is incremental as it builds on existing statistical methods.

The paper tackled the challenge of structural and morphological divergence in English to Indian language machine translation by using pre-ordering and suffix separation, resulting in improved translation quality.

English to Indian language machine translation poses the challenge of structural and morphological divergence. This paper describes English to Indian language statistical machine translation using pre-ordering and suffix separation. The pre-ordering uses rules to transfer the structure of the source sentences prior to training and translation. This syntactic restructuring helps statistical machine translation to tackle the structural divergence and hence better translation quality. The suffix separation is used to tackle the morphological divergence between English and highly agglutinative Indian languages. We demonstrate that the use of pre-ordering and suffix separation helps in improving the quality of English to Indian Language machine translation.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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