Paper: A Context-Sensitive Model For Probabilistic LR Parsing Of Spoken Language With Transformation-Based Postprocessing

ACL ID C00-2098
Title A Context-Sensitive Model For Probabilistic LR Parsing Of Spoken Language With Transformation-Based Postprocessing
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2000
Authors

This paper describes a hybrid approach to spontaneous speech parsing. The implelnented parser uses an extended probabilistic LR parsing model with rich context and its output is post- processed by a symbolic tree transformation routine that tries to eliminate systematic errors of the parser. The parser has been trained for three different languages and was successflflly integrated in tile Verbmobil speech-to-speech translation system. The parser achieves more than 90%/90% labeled precision/recall on pmsed Verbmobil utterances while 3% of German and 5% of all English input caunot be parsed.