A neural model of auditory scene analysis and source segregation
نویسندگان
چکیده
منابع مشابه
ARTSTREAM: a neural network model of auditory scene analysis and source segregation
Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noise. The auditory system is capable of teasing apart these sources into distinct mental objects, or streams. Such an 'auditory scene analysis' enables the brain to solve the cocktail party problem. A neural network model of auditory scene analysis, called the ARTSTREAM model, is presented to propo...
متن کاملARSTREAM: A Neural Network Model of Auditory Scene Analysis and Source Segregation
Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noise. The auditory system is capable of teasing apart these sources into distinct mental objects, or streams. Such an "auditory scene analysis" enables the brain to solve the cocktail party problem. A neural network model of auditory scene analysis, called the ARTSTREAM model, is presented to propo...
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Assessment of the neural correlates of auditory scene analysis, using an index of sound change detection that does not require the listener to attend to the sounds [a component of event-related brain potentials called the mismatch negativity (MMN)], has previously demonstrated that segregation processes can occur without attention focused on the sounds and that within-stream contextual factors ...
متن کاملA computational model of auditory scene analysis
Various grouping attributes have been translated into successful signal processing techniques that may be used in source separation, e.g., to separate speech from background. However, separation is not enough to know: What is the source of the sound? A next step beyond primitive ASA is schema-based ASA, to give meaning to the source, i.e. to map bottom-up audio features to the meaningful conten...
متن کاملImproved monaural speech segregation based on computational auditory scene analysis
A lot of effort has been made in Computational Auditory Scene Analysis (CASA) to segregate target speech from monaural mixtures. Based on the principle of CASA, this article proposes an improved algorithm for monaural speech segregation. To extract the energy feature more accurately, the proposed algorithm improves the threshold selection for response energy in initial segmentation stage. Since...
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ژورنال
عنوان ژورنال: The Journal of the Acoustical Society of America
سال: 1995
ISSN: 0001-4966
DOI: 10.1121/1.414160