Anusaaraka: Machine Translation in Stages

TL;DR

Anusaaraka proposes a staged approach to machine translation that acknowledges the challenges of fully-automatic high-quality translation due to the complexity of interpretation and contextual understanding.

Contribution

The paper introduces a multi-stage translation framework that addresses the limitations of current fully-automatic systems by breaking down the translation process.

Findings

Highlights the difficulty of achieving fully-automatic high-quality translation.

Emphasizes the importance of interpretation and context in translation.

Proposes a staged approach to improve translation accuracy.

Abstract

Fully-automatic general-purpose high-quality machine translation systems (FGH-MT) are extremely difficult to build. In fact, there is no system in the world for any pair of languages which qualifies to be called FGH-MT. The reasons are not far to seek. Translation is a creative process which involves interpretation of the given text by the translator. Translation would also vary depending on the audience and the purpose for which it is meant. This would explain the difficulty of building a machine translation system. Since, the machine is not capable of interpreting a general text with sufficient accuracy automatically at present - let alone re-expressing it for a given audience, it fails to perform as FGH-MT. FOOTNOTE{The major difficulty that the machine faces in interpreting a given text is the lack of general world knowledge or common sense knowledge.}