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2008
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A top-down auditory attention model for learning task dependent influences on prominence detection in speech

10 years 4 months ago
A top-down auditory attention model for learning task dependent influences on prominence detection in speech
A top-down task-dependent model guides attention to likely target locations in cluttered scenes. Here, a novel biologically plausible top-down auditory attention model is presented to model such taskdependent influences on a given task. First, multi-scale features are extracted based on the processing stages in the central auditory system, and converted to low-level auditory “gist” features. These features capture rough information about the overall scene. Then, the top-down model learns the mapping between auditory gist features and the scene categories. The proposed top-down attention model is tested with prominent syllable detection task in speech. When tested on broadcast news-style read speech using the BU Radio News Corpus, the model achieves 85.8% prominence detection accuracy at syllable level. The results compare well to the reported human performance on this task.
Ozlem Kalinli, Shrikanth S. Narayanan
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICASSP
Authors Ozlem Kalinli, Shrikanth S. Narayanan
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