The BBN Spoken Language System

Boisen, Sean; Chow, Yen‐Lu; Haus, Andrew; Ingria, Robert; Roukas, Salim; Stallard, David

doi:10.3115/100964.100970

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…Recently, we have begun porting our ACFG natural language system (Boisen, et al, 1989b) to a personnel database domain, a domain for which Parlance had been configured using the Learner. This raised the possibility of using the output files created by the Learner as knowledge sources for components of the ACFG system.…”

Section: The Learnermentioning

confidence: 99%

Porting to new domains using the Learner#8482;

Ingria¹,

Ramshaw²

1989

Proceedings of the Workshop on Speech and Natural Language - HLT '89

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Section: The Learnermentioning

confidence: 99%

Porting to new domains using the Learner#8482;

Ingria¹,

Ramshaw²

1989

Proceedings of the Workshop on Speech and Natural Language - HLT '89

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“…(le) is ungrammatical, then, since the values singular and plural cannot unify and the fact that "sheep" must agree with both "is" and "are" in number would require their unification. This illegal feature configuration is shown in (2).…”

Section: Introductionmentioning

confidence: 99%

The limits of unification

Ingria¹

1990

Proceedings of the 28th Annual Meeting on Association for Computational Linguistics -

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Current complex-feature based grammars use a single procedure-unification-for a multitude of purposes, among them, enforcing formal agreement between purely syntactic features. This paper presents evidence from several natural languages that unification-variable-matching combined with variable substitution-is the wrong mechanism for effecting agreement. The view of grammar developed here is one in which unification is used for semantic interpretation, while purely formal agreement involves only a check for non-distinctness-i.e, variable-matching without variable substitution.

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“…However, since it adds no real linguistic constraints, it may produce many false positives (misinterpretation of the input ) . A second possiblity which has been explored at some sites [1] is to have the recognizer produce a word lattice, with (acoustic) transition probabilities between words. The language system can then search this lattice for the best candidate.…”

Section: Language Constraints During Recognitionmentioning

confidence: 99%

Integrating syntax and semantics into spoken language understanding

Hirschman¹,

Seneff²,

Goodine³

et al. 1991

Proceedings of the Workshop on Speech and Natural Language - HLT '91

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This paper describes several experiments combining natural language and acoustic constraints to improve overall performance of the MIT VOYAGER spoken language system. This system couples the SUMMIT speech recognition system with the TINA language understanding system to answer spoken queries about navigational assistance in the Cambridge, MA, area. The overall goal of our research is to combine acoustic, syntactic and semantic knowledge sources. Our first experiment showed improvement by combining acoustic score and parse probability normalized for number of terminals. Results were further improved by the use of an explicit rejection criterion based on normalized parse probabilities. The use of the combined parse/acoustic score, together with the rejection criterion, gave an improvement in overall score of more than 33% on both training and test data, where score is defined as percent correct minus percent incorrect. Experiments on a fully integrated system which uses the parser to predict possible next words to the recognizer are now underway.

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The BBN Spoken Language System

Cited by 5 publications

References 12 publications

Porting to new domains using the Learner#8482;

Porting to new domains using the Learner#8482;

The limits of unification

Integrating syntax and semantics into spoken language understanding

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