Accession Number:

ADA460276

Title:

Morphological Analysis for Statistical Machine Translation

Descriptive Note:

Corporate Author:

IBM THOMAS J WATSON RESEARCH CENTER YORKTOWN HEIGHTS NY

Personal Author(s):

Report Date:

2004-01-01

Pagination or Media Count:

5.0

Abstract:

We present a novel morphological analysis technique which induces a morphological and syntactic symmetry between two languages with highly asymmetrical morphological structures to improve statistical machine translation qualities. The technique pre-supposes fine-grained segmentation of a word in the morphologically rich language into the sequence of prefixes-stem-suffixes and part-of-speech tagging of the parallel corpus. The algorithm identifies morphemes to be merged or deleted in the morphologically rich language to induce the desired morphological and syntactic symmetry. The technique improves Arabic-to-English translation qualities significantly when applied to IBM Model 1 and Phrase Translation Models trained on the training corpus size ranging from 3,500 to 3.3 million sentence pairs.

Subject Categories:

  • Linguistics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE