-
Srihari, R.K.: Using speech input for image interpretation, annotation, and retrieval (1997)
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- Abstract
- Explores the interaction of textual and photographic information in an integrated text and image database environment and describes 3 different applications involving the exploitation of linguistic context in vision. Describes the practical application of these ideas in working systems. PICTION uses captions to identify human faces in a photograph, wile Show&Tell is a multimedia system for semi automatic image annotation. The system combines advances in speech recognition, natural language processing and image understanding to assist in image annotation and enhance image retrieval capabilities. Presents an extension of this work to video annotation and retrieval
- Date
- 22. 9.1997 19:16:05
- Source
- Digital image access and retrieval: Proceedings of the 1996 Clinic on Library Applications of Data Processing, 24-26 Mar 1996. Ed.: P.B. Heidorn u. B. Sandore
-
Wittbrock, M.J.; Hauptmann, A.G.: Speech recognition for a digital video library (1998)
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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
-
Kruschwitz, U.; AI-Bakour, H.: Users want more sophisticated search assistants : results of a task-based evaluation (2005)
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- Abstract
- The Web provides a massive knowledge source, as do intranets and other electronic document collections. However, much of that knowledge is encoded implicitly and cannot be applied directly without processing into some more appropriate structures. Searching, browsing, question answering, for example, could all benefit from domain-specific knowledge contained in the documents, and in applications such as simple search we do not actually need very "deep" knowledge structures such as ontologies, but we can get a long way with a model of the domain that consists of term hierarchies. We combine domain knowledge automatically acquired by exploiting the documents' markup structure with knowledge extracted an the fly to assist a user with ad hoc search requests. Such a search system can suggest query modification options derived from the actual data and thus guide a user through the space of documents. This article gives a detailed account of a task-based evaluation that compares a search system that uses the outlined domain knowledge with a standard search system. We found that users do use the query modification suggestions proposed by the system. The main conclusion we can draw from this evaluation, however, is that users prefer a system that can suggest query modifications over a standard search engine, which simply presents a ranked list of documents. Most interestingly, we observe this user preference despite the fact that the baseline system even performs slightly better under certain criteria.
-
Peters, B.F.: Online searching using speech as a man / machine interface (1989)
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- Source
- Information processing and management. 25(1989), S.391-406
-
Keller, F.: How do humans deal with ungrammatical input? : Experimental evidence and computational modelling (1996)
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- Source
- Natural language processing and speech technology: Results of the 3rd KONVENS Conference, Bielefeld, October 1996. Ed.: D. Gibbon
-
Marx, J.: ¬Die '¬Computer-Talk-These' in der Sprachgenerierung : Hinweise zur Gestaltung natürlichsprachlicher Zustandsanzeigen in multimodalen Informationssystemen (1996)
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- Source
- Natural language processing and speech technology: Results of the 3rd KONVENS Conference, Bielefeld, October 1996. Ed.: D. Gibbon
-
Schultz, T.; Soltau, H.: Automatische Identifizierung spontan gesprochener Sprachen mit neuronalen Netzen (1996)
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- Source
- Natural language processing and speech technology: Results of the 3rd KONVENS Conference, Bielefeld, October 1996. Ed.: D. Gibbon
-
Thompson, L.A.; Ogden, W.C.: Visible speech improves human language understanding : implications for speech processing systems (1995)
0.01
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- Abstract
- Presents evidence from the study of human language understanding suggesting that the ability to perceive visible speech can greatly influence the ability to understand and remember spoken language. A view of the speaker's face can greatly aid in the perception of ambiguous or noisy speech and can aid cognitive processing of speech leading to better understanding and recall. Some of these effects have been replaced using computer synthesized visual and auditory speech. When giving an interface a voice, it may be best to give it a face too
-
Hannabuss, S.: Dialogue and the search for information (1989)
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- Abstract
- Knowledge of conversation theory and speech act assists us to understand how people search for information. Dialogue embodies meanings and intentionalities, and represents epistemic inquiry. There are implications for the information-processing model of cognitive psychology. Question formulation (erotetics) and turn-taking play important roles in eliciting information, while discourse analysis furnishes us with information about people's categorising, recall, and semantic skills
-
Sparck Jones, K.; Jones, G.J.F.; Foote, J.T.; Young, S.J.: Experiments in spoken document retrieval (1996)
0.01
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- Source
- Information processing and management. 32(1996) no.4, S.399-417
-
Young, C.W.; Eastman, C.M.; Oakman, R.L.: ¬An analysis of ill-formed input in natural language queries to document retrieval systems (1991)
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- Source
- Information processing and management. 27(1991) no.6, S.615-622
-
Ferret, O.; Grau, B.; Hurault-Plantet, M.; Illouz, G.; Jacquemin, C.; Monceaux, L.; Robba, I.; Vilnat, A.: How NLP can improve question answering (2002)
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- Abstract
- Answering open-domain factual questions requires Natural Language processing for refining document selection and answer identification. With our system QALC, we have participated in the Question Answering track of the TREC8, TREC9 and TREC10 evaluations. QALC performs an analysis of documents relying an multiword term searches and their linguistic variation both to minimize the number of documents selected and to provide additional clues when comparing question and sentence representations. This comparison process also makes use of the results of a syntactic parsing of the questions and Named Entity recognition functionalities. Answer extraction relies an the application of syntactic patterns chosen according to the kind of information that is sought, and categorized depending an the syntactic form of the question. These patterns allow QALC to handle nicely linguistic variations at the answer level.
-
Lin, J.; Katz, B.: Building a reusable test collection for question answering (2006)
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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."
