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A systematic comparison of various statistical alignment models
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Bidirectional decoding for statistical machine translation
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The Alignment Template Approach to Statistical Machine Translation
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Generation of word graphs in statistical machine translation
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A weighted finite state transducer translation template model for statistical machine translation
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An algorithmic framework for the decoding problem in statistical machine translation
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Efficient search for Inversion Transduction Grammar
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Theory of alignment generators and applications to statistical machine translation
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Generalized stack decoding algorithms for statistical machine translation
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Divide and translate: improving long distance reordering in statistical machine translation
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Exact decoding of phrase-based translation models through Lagrangian relaxation
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Document-wide decoding for phrase-based statistical machine translation
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In this paper, we describe an efficient A* search algorithm for statistical machine translation. In contrary to beam-search or greedy approaches it is possible to guarantee the avoidance of search errors with A*. We develop various so-phisticated admissible and almost admissible heuristic functions. Especially our newly developped method to perform a multi-pass A* search with an iteratively improved heuristic function allows us to translate even long sentences. We compare the A* search algorithm with a beam-search approach on the Hansards task.