Integration of diverse recognition methodologies through reevaluation of N-best sentence hypotheses
HLT '91 Proceedings of the workshop on Speech and Natural Language
Spoken Language Translator: First-Year Report
Spoken Language Translator: First-Year Report
BBN BYBLOS and HARC February 1992 ATIS benchmark results
HLT '91 Proceedings of the workshop on Speech and Natural Language
Recent improvements and benchmark results for the Paramax ATIS system
HLT '91 Proceedings of the workshop on Speech and Natural Language
A speech to speech translation system built from standard components
HLT '93 Proceedings of the workshop on Human Language Technology
Training and scaling preference functions for disambiguation
Computational Linguistics
Improving language models by clustering training sentences
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
Text segmentation with multiple surface linguistic cues
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Fast parsing using pruning and grammar specialization
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Error detection using linguistic features
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Filtering errors and repairing linguistic anomalies for spoken dialogue systems
ISDS '97 Interactive Spoken Dialog Systems on Bringing Speech and NLP Together in Real Applications
Third-party error detection support mechanisms for dictation speech recognition
Interacting with Computers
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A simple and general method is described that can combine different knowledge sources to reorder N-best lists of hypotheses produced by a speech recognizer. The method is automatically trainable, acquiring information from both positive and negative examples. In experiments, the method was tested on a 1000-utterance sample of unseen ATIS data.