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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 12 of 12 1 Toward Determining the Comprehensibility of Machine Translations Maney, Tucker; Sibert, Linda; Perzanowski, Dennis... In: DTIC (2012) BASE Show details 2 Novel Topic Impact on Authorship Attribution Caver, Johnnie F. In: DTIC (2009) BASE Show details 3 Syntactic Simplification for Improving Content Selection in Multi-Document Summarization Siddharthan, Advaith; Nenkova, Ani; McKeown, Kathleen In: DTIC (2004) BASE Show details 4 Cross-Document Coreference on a Large Scale Corpus Gooi, Chung H.; Allan, James In: DTIC (2004) BASE Show details 5 The Bible, Truth, and Multilingual OCR Evaluation Kanungo, Tapas; Resnik, Philip In: DTIC (1998) BASE Show details 6 Experiments in Spoken Document Retrieval at CMU Siegler, M. A.; Witbrock, M. J.; Slattery, S. T.... In: DTIC (1997) BASE Show details 7 Overview of Results of the MUC-6 Evaluation Sundheim, Beth M. In: DTIC (1995) BASE Show details 8 Phonological Parsing for Bi-directional Letter-to-Sound/Sound-to-Letter Generation Meng, Helen M.; Seneff, Stephanie; Zue, Victor W. In: DTIC (1994) Abstract: In this paper, we describe a reversible letter-to-sound/sound to-letter generation system based on an approach which combines a rule-based formalism with data-driven techniques. We adopt a probabilistic parsing strategy to provide a hierarchical lexical analysis of a word, including information such as morphology, stress, syllabification, phonemics and graphemics. Long-distance constraints are propagated by enforcing local constraints throughout the hierarchy. Our training and testing corpora are derived from the high-frequency portion of the Brown Corpus (10,000 words), augmented with markers indicating stress and word morphology. We evaluated our performance based on an unseen test set. The percentage of nonparsable words for letter-to-sound and sound-to-letter generation were 6% and 5% respectively. Of the remaining words our system achieved a word accuracy of 71.8% and a phoneme accuracy of 92.5% for letter-to-sound generation, and a word accuracy of 55.8% and letter accuracy of 89.4% for sound-to-letter generation. We also compared our hierarchical approach with an alternative, single-layer approach to demonstrate how the hierarchy provides a parsimonious description for English orthographic-phonological regularities, while simultaneously attaining competitive generation accuracy. ; Supported in part by DARPA. Keyword: *PARSERS; *WORDS(LANGUAGE); ACCURACY; COMPETITION; HIERARCHIES; INDICATORS; LEXICOGRAPHY; Linguistics; MARKERS; MORPHOLOGY; PHONETICS; PROBABILITY; STRATEGY; STRESSES; TEST SETS URL: http://www.dtic.mil/docs/citations/ADA458591 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA458591 BASE Hide details 9 Signal Processing for Robust Speech Recognition Liu, Fu-Hua; Moreno, Pedro J.; Stern, Richard M.... In: DTIC (1994) BASE Show details 10 Adaptive Natural Language Processing Ayuso, Damaris; Boisen, Sean; Bobrow, Robert... In: DTIC AND NTIS (1991) BASE Show details 11 Integrating Syntax, Semantics,and Discourse DARPA (Defense Advanced Research Projects Agency) Natural Language Understanding Program Hirschman, Lynette In: DTIC AND NTIS (1989) BASE Show details 12 Integration of Speech and Natural Language Boisen, S.; Chow, Y.; Haas, A.... In: DTIC AND NTIS (1989) BASE Show details

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