Conference Paper

Rule Filtering by Pattern for Efficient Hierarchical Translation.

DOI: 10.3115/1609067.1609109 Conference: EACL 2009, 12th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference, March 30 - April3, 2009, Athens, Greece
Source: DBLP


We describe refinements to hierarchical translation search procedures intended to reduce both search errors and memory us- age through modifications to hypothesis expansion in cube pruning and reductions in the size of the rule sets used in transla- tion. Rules are put into syntactic classes based on the number of non-terminals and the pattern, and various filtering strate- gies are then applied to assess the impact on translation speed and quality. Results are reported on the 2008 NIST Arabic-to- English evaluation task. lation. Memory usage can be reduced in cube pruning (Chiang, 2007) through smart memoiza- tion, and spreading neighborhood exploration can be used to reduce search errors. However, search errors can still remain even when implementing simple phrase-based translation. We describe a 'shallow' search through hierarchical rules which greatly speeds translation without any effect on quality. We then describe techniques to analyze and reduce the set of hierarchical rules. We do this based on the structural properties of rules and develop strategies to identify and remove redun- dant or harmful rules. We identify groupings of rules based on non-terminals and their patterns and assess the impact on translation quality and com- putational requirements for each given rule group. We find that with appropriate filtering strategies rule sets can be greatly reduced in size without im- pact on translation performance.

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    • "The word alignments for Chinese→English translation are trained from around 250M words of parallel text distributed for the GALE P3 evaluation. Hierarchical rules are extracted from the aligned text using the constraints described in Chiang (2007) with the count and pattern filters of Iglesias et al. (2009a). Firstpass translation decoding with HiFST (Iglesias et al. 2009b) generates word lattices encoding large numbers of alternative hypotheses. "
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    • "Secondly, they also employ pattern-based filtering (Iglesias et al., 2009) in order to reducing redundancies in the Hiero grammar by filtering it based on certain rule patterns. However in our limited experiments , we observed the filtered grammar to perform worse than the full grammar, as also noted by (Zollmann et al., 2008). "
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    ABSTRACT: Shallow-n grammars (de Gispert et al., 2010) were introduced to reduce over-generation in the Hiero translation model (Chiang, 2005) resulting in much faster decoding and restricting reordering to a desired level for specific language pairs. However, Shallow-n grammars require parameters which cannot be directly optimized using minimum error-rate tuning by the decoder. This paper introduces some novel improvements to the translation model for Shallow-n grammars. We introduce two rules: a BITG-style reordering glue rule and a simpler monotonic concatenation rule. We use separate features for the new rules in our log-linear model allowing the decoder to directly optimize the feature weights. We show this formulation of Shallow-n hierarchical phrase-based translation is comparable in translation quality to full Hiero-style decoding (without shallow rules) while at the same time being considerably faster.
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    • "The parallel corpus is aligned using MTTK (Deng and Byrne, 2008) in both source-to-target and target-to-source directions. We then follow standard heuristics (Chiang, 2007) and filtering strategies (Iglesias et al., 2009b) to extract hierarchical phrases from the union of the directional word alignments . We call a translation grammar the set of rules extracted from this process. "
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    ABSTRACT: This paper compares several translation representations for a synchronous context-free grammar parse including CFGs/hypergraphs, finite-state automata (FSA), and pushdown automata (PDA). The representation choice is shown to determine the form and complexity of target LM intersection and shortest-path algorithms that follow. Intersection, shortest path, FSA expansion and RTN replacement algorithms are presented for PDAs. Chinese-to-English translation experiments using HiFST and HiPDT, FSA and PDA-based decoders, are presented using admissible (or exact) search, possible for HiFST with compact SCFG rulesets and HiPDT with compact LMs. For large rulesets with large LMs, we introduce a two-pass search strategy which we then analyze in terms of search errors and translation performance.
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