Concept framework for audio information retrieval: ARF
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The majority of researches on content-based retrieval focused on visual media. However audio is also an important medium and information carrier from the viewpoint of human auditory perception, so it is needed to retrieve for audio collection. Audio is handled by conventional methods as an opaque stream medium, which is not suitable for information retrieval by its content. In fact, audio carries rich aural information with the form of speech, musical, and sound effects, so it could be retrieved based on its aural content, such as acoustic features, musical melodies and associated semantics. In this paper, a concept framework (ARF) for content-based audio retrieval is proposed from systematic perspectives, which describes audio content model, audio retrieval architecture and audio query schemes. Audio contents are represented by a hierarchical model and a set of formal descriptions from physical to acoustic to semantic level, which depict acoustic features, logical structure and semantics of audio and audio objects. The architecture consisting of audio meta-database, populating and accessing modules presents a system structure view of audio information retrieval. The query schemes give generalized approaches and modes concerning how users deliver audio information needs to audio collections. Finally, an audio retrieval example implemented is used to explain and specify the application of the components in the proposed ARF.
KeywordsARF audio information retrieval content-based retrieval multimedia information retrieval
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- ISO/IEC JTC1/SC29/WG11. MPEG-7 applications. N4676, Mar. 2002, Jeju, Korea.Google Scholar
- Ricardo Baeza-Yates, Berthier Ribeiro-Neto. Modern Information Retrieval. Addison-Wesley Longman Limited. 1999.Google Scholar
- Erling Woodet al. Content based classification, search, and retrieval of audic.IEEE Multimedia, 1996.Google Scholar
- Wactlar H, Hauptmann A, Witbrock M. Informedia: News-on-demand experiments in speech recognition. InProc. ARPA Speech Recognition Workshop, Arden House, Harriman, NY, Feb. 18–21, 1996.Google Scholar
- Brown M G, Foote J T, Jones G J Fet al. Video mail retrieval by voice: An overview of the Cambridge/ Olivetti retrieval system. InProc. 2nd ACM Int. Conf. Multimedia Workshop on Multimedia Data-Base Management, San Francisco USA, October, 1994, pp.47–55.Google Scholar
- Laura Slaughteret al. A graphical interface for speech-based retrieval. InProc. the Third ACM Digital Library Conference, Pittsburgh, PA, June, 1998.Google Scholar
- McNab R J, Smith L A, Witten I H. Signal processing for melody transcription. InProc. Australian Computer Science Conference, Melbourne, Australia, January, 1996, pp.301–307.Google Scholar
- Ruben Gonzalez, Kathy Melin. Content-based retrieval of audio. InProc. Australian Telecommunication Networks & Applications Conference, 1996, pp.357–362.Google Scholar
- Jonathan Foote. Content-based retrieval of music and audio. InProc. SPIE, Multimedia Storage and Archiving Systems II, 1997, 3229: 138–147.Google Scholar
- Guohui Li, Ashfaq A. Khokhar. Content-based indexing and retrieval of audio data using wavelet. InProc. IEEE International Conference on Multimedia and Expro (ICME'2000), August 2000, New York, pp.885–888.Google Scholar
- ISO/IEC JTC1/SC29/WG11. MPEG-7 Overview. Doc. N4980, Klangenfurt, July 2002.Google Scholar