Efficient Algorithms for Richer Formalisms: Parsing and Machine Translation
نویسنده
چکیده
My PhD research has been on the algorithmic and formal aspects of computational linguistics, esp. in the areas of parsing and machine translation. I am interested in developing efficient algorithms for formalisms with rich expressive power, so that we can have a better modeling of human languages without sacrificing efficiency. In doing so, I hope to help integrating more linguistic and structural knowledge with modern statistical techniques, and in particular, for syntax-based machine translation (MT) systems. Among other projects, I have been working on kbest parsing, synchronous binarization, and syntaxdirected translation.
منابع مشابه
Alto: Rapid Prototyping for Parsing and Translation
We present Alto, a rapid prototyping tool for new grammar formalisms. Alto implements generic but efficient algorithms for parsing, translation, and training for a range of monolingual and synchronous grammar formalisms. It can easily be extended to new formalisms, which makes all of these algorithms immediately available for the new formalism.
متن کاملGeneral binarization for parsing and translation
Binarization of grammars is crucial for improving the complexity and performance of parsing and translation. We present a versatile binarization algorithm that can be tailored to a number of grammar formalisms by simply varying a formal parameter. We apply our algorithm to binarizing tree-to-string transducers used in syntax-based machine translation.
متن کاملبرچسبزنی خودکار نقشهای معنایی در جملات فارسی به کمک درختهای وابستگی
Automatic identification of words with semantic roles (such as Agent, Patient, Source, etc.) in sentences and attaching correct semantic roles to them, may lead to improvement in many natural language processing tasks including information extraction, question answering, text summarization and machine translation. Semantic role labeling systems usually take advantage of syntactic parsing and th...
متن کاملDiscriminative Feature-Rich Modeling for Syntax-Based Machine Translation
State-of-the-art statistical machine translation systems are most frequently built on phrasebased (Koehn et al., 2003) or hierarchical translation models (Chiang, 2005). In addition, a wide variety of models exploiting syntactic annotation on either the source or target side (or both) have recently been developed and also give state-of-the-art performance (Galley et al., 2006; Zollmann and Venu...
متن کاملA Generalized View on Parsing and Translation
We present a formal framework that generalizes a variety of monolingual and synchronous grammar formalisms for parsing and translation. Our framework is based on regular tree grammars that describe derivation trees, which are interpreted in arbitrary algebras. We obtain generic parsing algorithms by exploiting closure properties of regular tree languages.
متن کامل