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Titlebook: Intelligent Audio Analysis; Björn W. Schuller Book 2013 Springer-Verlag Berlin Heidelberg 2013 Audio Enhancement.Audio Robustness.Audio So

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Applications in Intelligent Music Analysisormance benchmarks. These comprise drum-beat separation, onset detection, tempo, metre, ballroom dance style, and mood determination, key and chord recognition, and structure analysis alongside singer trait classification. The latter includes singer age, gender, race, and height recognition.
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Book 2013d methods and discusses the typical Intelligent Audio Analysis chain going from audio data to audio features to audio recognition.  Further, an introduction to audio source separation, and enhancement and robustness are given. .After the introductory parts, the book shows several applications for th
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Applications in Intelligent Speech Analysissation recognition, paralinguistic speaker states and traits as exemplified by sentiment, emotion, interest, age, gender, intoxication and sleepiness. All examples stem from the author’s recent work. In particular the latter are chosen from a series of Challenges co-organised by the author at Interspeech from 2009 onwards.
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Visioncognition. Further, continuous writer sentiment, and speaker interest and height determination as well as sound listener induced arousal and valence prediction are contained. Based on these performances, future perspectives are given.
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https://doi.org/10.1007/978-3-642-36806-6Audio Enhancement; Audio Robustness; Audio Source Separation; Fully Automatic Chunking; Music Informatio
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Intelligent Audio Analysis978-3-642-36806-6Series ISSN 1860-4862 Series E-ISSN 1860-4870
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Intelligent Audio Analysis: A DefinitionA definition of Intelligent Audio Analysis is given. Further, real-life conditions are defined comprising the aspects of non-prototypical and non-preselected independent test data that has never been used during optimisation, and fully automatic processing.
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