GLR-Parsing of Word Lattices Using a Beam Search Method

This paper presents an approach that allows the efficient integration of speech recognition and language understanding using Tomita's generalized LR-parsing algorithm. For this purpose the GLRP-algorithm is revised so that an agenda mechanism can be used to control the flow of computation of the parsing process. This new approach is used to integrate speech recognition and speech understanding incrementally with a beam search method. These considerations have been implemented and tested on ten word lattices.Comment: 4 pages, 61K postscript, compressed, uuencoded, Eurospeech 9/95, Madri

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本文データは平成22年度国立国会図書館の学位論文(博士)のデジタル化実施により作成された画像ファイルを基にpdf変換したものである京都大学0048新制・論文博士博士(工学)乙第8652号論工博第2893号新制||工||968(附属図書館)UT51-94-R411(主査)教授 長尾 真, 教授 堂下 修司, 教授 池田 克夫学位規則第4条第2項該当Doctor of EngineeringKyoto UniversityDFA

GLR parsing with multiple grammars for natural language queries.

Luk Po Chui.Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.Includes bibliographical references (leaves 97-100).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Efficiency and Memory --- p.2Chapter 1.2 --- Ambiguity --- p.3Chapter 1.3 --- Robustness --- p.4Chapter 1.4 --- Thesis Organization --- p.5Chapter 2 --- Background --- p.7Chapter 2.1 --- Introduction --- p.7Chapter 2.2 --- Context-Free Grammars --- p.8Chapter 2.3 --- The LR Parsing Algorithm --- p.9Chapter 2.4 --- The Generalized LR Parsing Algorithm --- p.12Chapter 2.4.1 --- Graph-Structured Stack --- p.12Chapter 2.4.2 --- Packed Shared Parse Forest --- p.14Chapter 2.5 --- Time and Space Complexity --- p.16Chapter 2.6 --- Related Work on Parsing --- p.17Chapter 2.6.1 --- GLR* --- p.17Chapter 2.6.2 --- TINA --- p.18Chapter 2.6.3 --- PHOENIX --- p.19Chapter 2.7 --- Chapter Summary --- p.21Chapter 3 --- Grammar Partitioning --- p.22Chapter 3.1 --- Introduction --- p.22Chapter 3.2 --- Motivation --- p.22Chapter 3.3 --- Previous Work on Grammar Partitioning --- p.24Chapter 3.4 --- Our Grammar Partitioning Approach --- p.26Chapter 3.4.1 --- Definitions and Concepts --- p.26Chapter 3.4.2 --- Guidelines for Grammar Partitioning --- p.29Chapter 3.5 --- An Example --- p.30Chapter 3.6 --- Chapter Summary --- p.34Chapter 4 --- Parser Composition --- p.35Chapter 4.1 --- Introduction --- p.35Chapter 4.2 --- GLR Lattice Parsing --- p.36Chapter 4.2.1 --- Lattice with Multiple Granularity --- p.36Chapter 4.2.2 --- Modifications to the GLR Parsing Algorithm --- p.37Chapter 4.3 --- Parser Composition Algorithms --- p.45Chapter 4.3.1 --- Parser Composition by Cascading --- p.46Chapter 4 3.2 --- Parser Composition with Predictive Pruning --- p.48Chapter 4.3.3 --- Comparison of Parser Composition by Cascading and Parser Composition with Predictive Pruning --- p.54Chapter 4.4 --- Chapter Summary --- p.54Chapter 5 --- Experimental Results and Analysis --- p.56Chapter 5.1 --- Introduction --- p.56Chapter 5.2 --- Experimental Corpus --- p.57Chapter 5.3 --- ATIS Grammar Development --- p.60Chapter 5.4 --- Grammar Partitioning and Parser Composition on ATIS Domain --- p.62Chapter 5.4.1 --- ATIS Grammar Partitioning --- p.62Chapter 5.4.2 --- Parser Composition on ATIS --- p.63Chapter 5.5 --- Ambiguity Handling --- p.66Chapter 5.6 --- Semantic Interpretation --- p.69Chapter 5.6.1 --- Best Path Selection --- p.69Chapter 5.6.2 --- Semantic Frame Generation --- p.71Chapter 5.6.3 --- Post-Processing --- p.72Chapter 5.7 --- Experiments --- p.73Chapter 5.7.1 --- Grammar Coverage --- p.73Chapter 5.7.2 --- Size of Parsing Table --- p.74Chapter 5.7.3 --- Computational Costs --- p.76Chapter 5.7.4 --- Accuracy Measures in Natural Language Understanding --- p.81Chapter 5.7.5 --- Summary of Results --- p.90Chapter 5.8 --- Chapter Summary --- p.91Chapter 6 --- Conclusions --- p.92Chapter 6.1 --- Thesis Summary --- p.92Chapter 6.2 --- Thesis Contributions --- p.93Chapter 6.3 --- Future Work --- p.94Chapter 6.3.1 --- Statistical Approach on Grammar Partitioning --- p.94Chapter 6.3.2 --- Probabilistic modeling for Best Parse Selection --- p.95Chapter 6.3.3 --- Robust Parsing Strategies --- p.96Bibliography --- p.97Chapter A --- ATIS-3 Grammar --- p.101Chapter A.l --- English ATIS-3 Grammar Rules --- p.101Chapter A.2 --- Chinese ATIS-3 Grammar Rules --- p.10