Robust detection and classification of objects in audio using limited training data
A method (200) and apparatus (100) for classifying a homogeneous audio segment are disclosed. The homogeneous audio comprises a sequence of audio samples (x(n)). The method (200) starts by forming a sequence of frames (701-704) along the sequence of audio samples (x(n)), each frame (701-704) compris...
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Sprache: | eng |
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Zusammenfassung: | A method (200) and apparatus (100) for classifying a homogeneous audio segment are disclosed. The homogeneous audio comprises a sequence of audio samples (x(n)). The method (200) starts by forming a sequence of frames (701-704) along the sequence of audio samples (x(n)), each frame (701-704) comprising a plurality of the audio samples (x(n)). The homogeneous audio segment is next divided (206) into a plurality of audio clips (711-714), with each audio clip being associated with a plurality of the frames (701-704). The method (200) then extracts (208) at least one frame feature for each clip (711-714). A clip feature vector (f) is next extracted from frame features of frames associated with the audio clip (711-714). Finally the segment is classified based on a continuous function defining the distribution of the clip feature vectors (f). |
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