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Audio fingerprinting is defined as a condensed digital summary to establish the equality or similarity of two audio objects. By comparing the fingerprinting of a query fragment of a few seconds with those stored in a fingerprinting database, the system returns matching results and related metadata. Besides this query-by-example application, this technology can also be used to monitor broadcast and detect copyrighted material. Audio fingerprinting is best known for its ability to link unlabeled audio to corresponding meta-data (e.g. artist and song name), regardless of the audio format. Audio…mehr

Produktbeschreibung
Audio fingerprinting is defined as a condensed digital summary to establish the equality or similarity of two audio objects. By comparing the fingerprinting of a query fragment of a few seconds with those stored in a fingerprinting database, the system returns matching results and related metadata. Besides this query-by-example application, this technology can also be used to monitor broadcast and detect copyrighted material. Audio fingerprinting is best known for its ability to link unlabeled audio to corresponding meta-data (e.g. artist and song name), regardless of the audio format. Audio fingerprinting or content-based audio identification (CBID) systems extract a perceptual digest of a piece of audio content, i.e. a fingerprint and store it in a database. When presented with unlabeled audio, its fingerprint is calculated and matched against those stored in the database. For the reader new to analysis of data a very short introduction is now provided on hierarchical clustering
Autorenporträt
Mr. M. Muni Sankar received his M.Tech degree in Digital Electronics and communication systems from JNTU, Anantapur, India in 2012. He is currently working as an Assistant Professor in the Department of ECE, SoET, SPMVV, Tirupati, India. Muni Sankar also published couples of research articles and journals in international repute.