Statistical Machine Translation by Parsing

نویسنده

  • I. Dan Melamed
چکیده

In an ordinary syntactic parser, the input is a string, and the grammar ranges over strings. This paper explores generalizations of ordinary parsing algorithms that allow the input to consist of string tuples and/or the grammar to range over string tuples. Such algorithms can infer the synchronous structures hidden in parallel texts. It turns out that these generalized parsers can do most of the work required to train and apply a syntax-aware statistical machine translation system.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Non-Projective Parsing for Statistical Machine Translation

We describe a novel approach for syntaxbased statistical MT, which builds on a variant of tree adjoining grammar (TAG). Inspired by work in discriminative dependency parsing, the key idea in our approach is to allow highly flexible reordering operations during parsing, in combination with a discriminative model that can condition on rich features of the sourcelanguage string. Experiments on tra...

متن کامل

Local Search with Very Large-Scale Neighborhoods for Optimal Permutations in Machine Translation∗

We introduce a novel decoding procedure for statistical machine translation and other ordering tasks based on a family of Very Large-Scale Neighborhoods, some of which have previously been applied to other NP-hard permutation problems. We significantly generalize these problems by simultaneously considering three distinct sets of ordering costs. We discuss how these costs might apply to MT, and...

متن کامل

Syntax-Directed Phrase-based Statistical Machine Translation

The SDTS has been applied in the field of compiler and in transfer-based machine translation. After the parsing step, the syntactic structure of a sentence is identified. The parse tree will be analyzed, augmented, and transformed by later phases in the SMT system. Those phases are controlled by syntax. We use the stochastic SDTS to model such kind of translation process for phrase-based SMT. T...

متن کامل

Learning for Semantic Parsing with Statistical Machine Translation

We present a novel statistical approach to semantic parsing, WASP, for constructing a complete, formal meaning representation of a sentence. A semantic parser is learned given a set of sentences annotated with their correct meaning representations. The main innovation of WASP is its use of state-of-the-art statistical machine translation techniques. A word alignment model is used for lexical ac...

متن کامل

Algorithms for Syntax-Aware Statistical Machine Translation

All of the non-trivial algorithms that are necessary for building and applying a rudimentary syntax-aware statistical machine translation system are generalized parsers. This paper extends the “translation by parsing” architecture by adding two components that are invariably used by state-of-the-art statistical machine translation systems. First, the paper shows how a generic syntax-aware trans...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004