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Hinz, H. Kirchhoffer, D. Marpe and T. Wiegand, Technical description of the HHI proposal for SVC CE1, ISO/IEC JTC 1/SC29/WG11, doc. M11244, Palma de Mallorca, Spain, Oct. 2004. 14. J. Reichel, M. Wien and H. 0, ISO/IEC JTC 1/SC29/WG11, doc. N6716, Palma de Mallorca, Spain, Oct. 2004. 15. H. Schwarz, D. Marpe and T. Wiegand: SVC overview, Joint Video Team, Doc. JVT-U145, Hangzhou (China), Oct. 2006. 16. Y. R. Reibman and S. Lin, Multiple description coding for video delivery, Proceedings of IEEE, vol.

For instance, efforts are currently invested on building a responsive machine capable of providing the services and responses of a human who understands the information content of the sound signal. Although these applications will be explored in detail below, we mention here the characteristic cases of automatic speech/speaker recognition, acoustic monitoring of machines, music content indexing and retrieval, acoustic surveillance, music transcription and context recognition by robots. In brief, in this chapter we present a thorough review of the general application area of sound classification as well as the feature extraction methods and pattern recognition techniques that have been particularly intense in the diverse application areas of general audio classification.

30–44, Apr. 1991. 52. S. W. Marcellin, JPEG2000: Fundamentals, Standards and Practice. Kluwer, Boston, 2002. 53. R. Koenen, Overview of the MPEG-4 standard, ISO/IEC JTC1/SC29/WG11 N3156, Maui, Dec. 1999. gr Summary. This chapter surveys the contemporary approaches of automatic sound recognition and discusses the benefits stemming from real-world applications of this technology. We identify the common aspects and subtle differences among these diverse application areas and review state-of-the-art systems.

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