Abstract
This paper describes the successful metamorphosis of PAGE from a string-based grammar development system to an efficient run time system, operating on word hypotheses graphs (WHGs). In particular, we report on the techniques we have applied to PAGE and which have resulted into a speed-up in parsing time of more than an order of magnitude. We elaborate how the system is interfaced to other components; WHG search, prosody detector, and robust semantic processing. We also present measurements for string and WHG parsing. The system as described in the paper has been applied in the speech translation project Verbmobil with large HPSG grammars for English, German, and Japanese.
The research described in this paper has greatly benefited from a fruitful collaboration with the HPSG group of CSLI at Stanford University. Especially we want to thank John Carroll, Rob Malouf, and Stephan Oepen. This research was supported by the German Federal Ministry for Education, Science, Research and Technology (BMBF) under grant no. 01 IV 701 V0.
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Kiefer, B., Krieger, HU., Nederhof, MJ. (2000). Efficient and Robust Parsing of Word Hypotheses Graphs. In: Wahlster, W. (eds) Verbmobil: Foundations of Speech-to-Speech Translation. Artificial Intelligence. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04230-4_20
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DOI: https://doi.org/10.1007/978-3-662-04230-4_20
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