Enhanced multimedia content access and exploitation using semantic speech retrieval

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    Abstract

    Techniques for automatic annotation of spoken content making use of speech recognition technology have long been characterized as holding unrealized promise to provide access to archives inundated with undisclosed multimedia material. This paper provides an overview of techniques and trends in semantic speech retrieval, which is taken to encompass all approaches offering meaning-based access to spoken word collections. We present descriptions, examples and insights for current techniques, including facing real-world heterogenity, aligning parallel resources and exploiting collateral collections. We also discuss ways in which speech recognition technology can be used to create multimedia connections that make new modes of access available to users. We conclude with an overview of the challenges for semantic speech retrieval in the workflow of a real-world archive and perspectives on future tasks in which speech retrieval integrates information related to affect and appeal, dimensions that transcend topic.
    Original languageUndefined
    Title of host publicationProceedings of the Third IEEE International Conference on Semantic Computing
    Place of PublicationBerkeley
    PublisherIEEE Computer Society Press
    Pages521-528
    Number of pages8
    ISBN (Print)978-0-7695-3800-6
    DOIs
    Publication statusPublished - Sep 2009
    EventThird IEEE International Conference on Semantic Computing, ICSC - Berkeley, CA, USA
    Duration: 14 Sep 200916 Sep 2009

    Publication series

    Name
    PublisherIEEE Computer Society Press

    Conference

    ConferenceThird IEEE International Conference on Semantic Computing, ICSC
    Period14/09/0916/09/09
    Other14-16 Sep 2009

    Keywords

    • METIS-264028
    • IR-68255
    • Spoken content
    • Speech Recognition
    • HMI-MR: MULTIMEDIA RETRIEVAL
    • multimedia retrieval and access
    • Semantics
    • EWI-16069
    • HMI-SLT: Speech and Language Technology
    • Speech retrieval

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