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AMAR: A Computational Model of Autosegmental Phonology
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In: DTIC AND NTIS (1993)
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| 242 |
Template Based Low Data Rate Speech Encoder
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In: DTIC AND NTIS (1993)
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| 243 |
Proceedings of the Association for Computing Machinery Special Interest Group for Ada Artificial Intelligence Working Group, 1992 Summer Workshop Held in Seattle, Washington on June 24-27, 1992
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In: DTIC AND NTIS (1993)
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| 244 |
ASR-9 Microburst Detection Algorithm
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In: DTIC AND NTIS (1993)
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| 245 |
Comparing Performance on Implicit Memory Tests
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In: DTIC AND NTIS (1993)
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| 246 |
Handwritten Word Recognition Based on Fourier Coefficients
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In: DTIC AND NTIS (1993)
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| 247 |
Dialog Structure and Plan Recognition in Spontaneous Spoken Dialog
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In: DTIC AND NTIS (1993)
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| 248 |
An Evaluation of Individual Empowerment and Self-Efficacy on Sexual Harrassment in the Work Environment
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In: DTIC AND NTIS (1993)
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| 249 |
Methods for Parallelizing Search Paths in Phrasing
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In: DTIC AND NTIS (1993)
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| 250 |
Talking to InterFIS: Adding Speech Input to a Natural Language Interface
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In: DTIC AND NTIS (1992)
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| 251 |
A Practical Methodology for the Evaluation of Spoken Language Systems
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In: DTIC (1992)
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| 252 |
Subject-Based Evaluation Measures for Interactive Spoken Language Systems
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In: DTIC (1992)
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| 253 |
Experiments in Evaluating Interactive Spoken Language Systems
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In: DTIC (1992)
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| 254 |
Tipster Shogun System (Joint GE-CMU): MUC-4 Test Results and Analysis
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In: DTIC (1992)
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| 255 |
GE-CMU: Description of the Tipster/Shogun System as Used for MUC-4
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In: DTIC (1992)
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| 256 |
BBN PLUM: MUC-4 Test Results and Analysis
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In: DTIC (1992)
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Abstract:
Our mid-term to long-term goals in data extraction from text for the next one to three years are to achieve much greater portability to new languages and new domains, greater robustness, and greater scalability. The novel aspect to our approach is the use of learning algorithms and probabilistic models to learn the domain-specific and language. specific knowledge necessary for a new domain and new language. Learning algorithms should contribute to scalability by making it feasible to deal with domains where it would be infeasible to invest sufficient human effort to bring a system up. Probabilistic models can contribute to robustness by allowing for words, constructions, and forms not anticipated ahead of time and by looking for the most likely interpretation in context. We began this research agenda approximately two years ago. During the last twelve months, we have focused much of our effort on porting our data extraction system (PLUM) to a new language (Japanese) and to two new domains. During the next twelve months, we anticipate porting PLUM to two or three additional domains. For any group to participate in MUC is a significant investment. To be consistent with our mid-term and long- term goals, we imposed the following constraints on ourselves in participating in MUC-4: * We would focus our effort on semi-automatically acquired knowledge. * We would minimize effort on handcrafted knowledge, and most generally. * We would minimize MUC-specific effort. Though the three self-imposed constraints meant our overall scores on the objective evaluation were not as high as if we had focused on handtuning and handcrafting the knowledge bases, MUC-4 became a vehicle for evaluating our progress on the long-term goals. ; Presented at the Message Understanding Conference (4th) (MUC-4), held in McLean, VA on 16-18 June 1992. Pub. in the Proceedings of Message Understanding Conference (4th) (MUC-4), 1992. Paper 92-1007. Sponsored in part by the Defense Advanced Research Projects Agency (DARPA).
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Keyword:
*INFORMATION RETRIEVAL; *KNOWLEDGE BASED SYSTEMS; *LANGUAGE TRANSLATION; *MATHEMATICAL MODELS; *MESSAGE UNDERSTANDING; *PROBABILISTIC LANGUAGE UNDERSTANDING MODELS; *TEXT PROCESSING; ALGORITHMS; COMPUTATIONAL LINGUISTICS; Cybernetics; GRAMMARS; Information Science; JAPANESE LANGUAGE; LEARNING ALGORITHMS; Linguistics; MARKOV MODELS; PARSERS; PARTIAL UNDERSTANDING; PLUM(PROBABILISTIC LANGUAGE UNDERSTANDING MODEL); PRECISION; PROBABILITY; RECALL; STATISTICAL ALGORITHMS; SYMPOSIA; TEST AND EVALUATION; TEXT CLASSIFICATION
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URL: http://www.dtic.mil/docs/citations/ADA460688
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA460688
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| 257 |
Journal of Rehabilitation Research and Development - Winter 1992. Volume 29, Number 1, 1992
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In: DTIC AND NTIS (1992)
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| 258 |
An Analysis of Proposed 97E10 Selection Characteristics
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In: DTIC AND NTIS (1992)
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| 259 |
Development of a Spoken Language System
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In: DTIC AND NTIS (1992)
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| 260 |
Diagnosing Knowledge States in Algebra Using the Rule Space Model
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In: DTIC AND NTIS (1992)
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