Titlebook: Machine Translation: From Research to Real Users; 5th Conference of th Stephen D. Richardson Conference proceedings 2002 Springer-Verlag Be

金盤是高原

Handling Translation Divergences: Combining Statistical and Symbolic Techniques in Generation-Heavy ion divergence problem is usually reserved for Transfer and Interlingual MT because it requires a large combination of complex lexical and structural mappings. A major requirement of these approaches is the accessibility of large amounts of explicit symmetric knowledge for both source and target lan

血統(tǒng)

使?jié)M足

Merging Example-Based and Statistical Machine Translation: An Experimentbeing able to say that machine translation fully meets the needs of real-life users. In a previous study [.], we have shown how a SMT engine could benefit from terminological resources, especially when translating texts very different from those used to train the system. In the present paper, we dis

AVERT

ATP861

Better Contextual Translation Using Machine Learningf between contextual specificity and general applicability of the mappings, which typically results in conflicting mappings without distinguishing context. We present a machine-learning approach to choosing between such mappings, using classifiers that, in effect, selectively expand the context for

STENT

Fast and Accurate Sentence Alignment of Bilingual Corporaither on sentence length or word correspondences. Sentence-length-based methods are relatively fast and fairly accurate. Word-correspondence-based methods are generally more accurate but much slower, and usually depend on cognates or a bilingual lexicon. Our method adapts and combines these approach

AXIOM

Deriving Semantic Knowledge from Descriptive Texts Using an MT SystemThe KANT system [.,.] was used to analyze input paragraphs, producing sentence-level interlingua representations. The interlinguas were merged to construct a paragraph-level representation, which was used to create a semantic network in Conceptual Graph (CG) [.] format. The interlinguas are also tra

沒血色

平淡而無味

Paleontology