We introduce SPMT, a new class of statistical Translation Models that use Syntactified target language Phrases. The SPMT models outperform a state of the art phrase-based baseline model by 2.64 Bleu points on the NIST 2003 Chinese-English test corpus and 0.28 points on a humanbased quality metric that ranks translations on a scale from 1 to 5.
In REF , it is demonstrated that 'syntactified' target language phrases can improve translation quality for Chinese-English.
SPMT: Statistical Machine Translation With Syntactified Target Language Phrases
Conference On Empirical Methods In Natural Language Processing
Computer Science