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  • × theme_ss:"Sprachretrieval"
  1. Lange, H.R.: Speech synthesis and speech recognition : tomorrow's human-computer interface? (1993) 0.03
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    Abstract
    State of the art review of techniques which employ speech as the human-computer interface focusing on current research, implementation and potential for 2 of the speech technologies: speech synthesis, or speech output from the computer; and speech recognition, or speech input to the computer. Provides an introduction to the subject, discusses speech synthesis and speech recognition, examines library applications and looks to future use and development of these technologies
    Source
    Annual review of information science and technology. 28(1993), S.153-185
  2. Lin, J.; Katz, B.: Building a reusable test collection for question answering (2006) 0.03
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    Abstract
    In contrast to traditional information retrieval systems, which return ranked lists of documents that users must manually browse through, a question answering system attempts to directly answer natural language questions posed by the user. Although such systems possess language-processing capabilities, they still rely on traditional document retrieval techniques to generate an initial candidate set of documents. In this article, the authors argue that document retrieval for question answering represents a task different from retrieving documents in response to more general retrospective information needs. Thus, to guide future system development, specialized question answering test collections must be constructed. They show that the current evaluation resources have major shortcomings; to remedy the situation, they have manually created a small, reusable question answering test collection for research purposes. In this article they describe their methodology for building this test collection and discuss issues they encountered regarding the notion of "answer correctness."
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.7, S.851-861
  3. Srihari, R.K.: Using speech input for image interpretation, annotation, and retrieval (1997) 0.02
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    Date
    22. 9.1997 19:16:05
    Imprint
    Urbana-Champaign, IL : Illinois University at Urbana-Champaign, Department of Library and Information Science
  4. Wittbrock, M.J.; Hauptmann, A.G.: Speech recognition for a digital video library (1998) 0.02
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    Abstract
    The standard method for making the full content of audio and video material searchable is to annotate it with human-generated meta-data that describes the content in a way that search can understand, as is done in the creation of multimedia CD-ROMs. However, for the huge amounts of data that could usefully be included in digital video and audio libraries, the cost of producing the meta-data is prohibitive. In the Informedia Digital Video Library, the production of the meta-data supporting the library interface is automated using techniques derived from artificial intelligence (AI) research. By applying speech recognition together with natural language processing, information retrieval, and image analysis, an interface has been prduced that helps users locate the information they want, and navigate or browse the digital video library more effectively. Specific interface components include automatc titles, filmstrips, video skims, word location marking, and representative frames for shots. Both the user interface and the information retrieval engine within Informedia are designed for use with automatically derived meta-data, much of which depends on speech recognition for its production. Some experimental information retrieval results will be given, supporting a basic premise of the Informedia project: That speech recognition generated transcripts can make multimedia material searchable. The Informedia project emphasizes the integration of speech recognition, image processing, natural language processing, and information retrieval to compensate for deficiencies in these individual technologies
    Source
    Journal of the American Society for Information Science. 49(1998) no.7, S.619-632
  5. Pomerantz, J.: ¬A linguistic analysis of question taxonomies (2005) 0.01
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.7, S.715-728
  6. Radev, D.; Fan, W.; Qu, H.; Wu, H.; Grewal, A.: Probabilistic question answering on the Web (2005) 0.01
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.6, S.571-583
  7. Kruschwitz, U.; AI-Bakour, H.: Users want more sophisticated search assistants : results of a task-based evaluation (2005) 0.00
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.13, S.1377-1393