Machine Listening
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Description: Reading list for an MIT seminar, most of the mentioned publications are directly available on their web server or linked to Amazon's book section.
Associate Professor of Music and Electrical Engineering Since audio signals are interpreted by the human ear-brain system, that complex perceptual mechanism should be simulated somehow in software for "machine listening". In other words, to perform on par with humans, the computer should hear and understand audio content much as humans do. Analyzing audio accurately involves several fields: electrical engineering (spectrum analysis, filtering, and audio transforms); psychoacoustics (sound perception); cognitive sciences (neuroscience and artificial intelligence); acoustics (physics of sound production); and music (harmony, rhythm, and timbre). Furthermore, audio transformations such as pitch shifting, time stretching, and sound object filtering, should be perceptually and musically meaningful. For best results, these transformations require perceptual understanding of spectral models, high-level feature extraction, and sound analysis/synthesis. Finally, structuring and coding the content of an audio file (sound and metadata) stand to benefit from efficient compression schemes, which discard inaudible information in the sound.
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| Page title: | Machine Listening |
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| IP-address: | 18.85.28.145 |
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| NS | Name Servers: USE2.AKAM.NET USE5.AKAM.NET |
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| Date | activated: 23-May-1985 last updated: 17-May-2013 expires: 31-Jul-2014 |