Learning translation templates from examples

LEARNING TRANSLATION TEMPLATES FROM EXAMPLESyH

Learning Translation Templates from Examples1

This paper proposes a mechanism for learning lexical level correspondences between two languages from a set of translated sentence pairs. The proposed mechanism is based on an analogical reasoning between two translation examples. Given two translation examples, the similar parts of the sentences in the source language must correspond the similar parts of the sentences in the target language. S...

Learning Translation Templates from Bilingual Texts

This paper proposes a mechanism for learning structural correspondences between two languages from a corpus of translated sentence pairs The proposed mechanism uses analogical reasoning between two translations Given a pair of translations the similar parts of the sentences in the source language must correspond the similar parts of the sentences in the target language Similarly the di erent pa...

Learning Translation Templates From Bilingual Text

This paper proposes a two-phase example-based machine translation methodology which develops translation templates from examples and then translates using template matching. This method improves translation quality and facilitates customization of machine translation systems. This paper focuses on the automatic learning of translation templates. A translation template is a bilingual pair of sen...

Title Learning templates from fuzzy examples in structural patternrecognition

Fuzzy-Attribute Graph (FAG) was proposed to handle fuzziness in the pattern primitives in structural pattern recogni~~on [l]. FAG has the advantage that we can combine several possible definition into a single template, and hence only one matching is required instead of one for each definition. Also, each vertex or edge of the graph can contain fuzzy attributes to model real-life situation. How...