We propose a novel technique for audio analytics and audio indexing using template based modeling of audio classes set in a one-pass dynamic programming continuous decoding framework. We propose use of concatenation costs in the one-pass DP recursions to reduce so-called incursion errors; we also propose selection of variable length templates for modeling indefinite duration audio classes using the segmental K-means (SKM) algorithm. Based on detailed decoding results with long audio streams, we conclude the effectiveness of template based modeling, SKM based template selection, 1-pass DP based decoding and the use of concatenation constraints therein. We show that an average (%Hit, %False-alarm) of (66%, 4.9%) are possible with the proposed decoding technique.
Bibliographic reference. Cherla, Srikanth / Ramasubramanian, V. (2010): "Audio analytics by template modeling and 1-pass DP based decoding", In INTERSPEECH-2010, 2230-2233.