Patent ID: 7634405

Claim:
A system that facilitates audio data recognition, comprising: an input sequence receiving component that receives at least one input sequence having individual events, the input sequence comprising an audio environment input, the individual events comprising individual sounds of the audio environment input; a representation component that employs an epitome to facilitate in constructing and representing a compressed representation of the input sequence that utilizes informative patch sampling to minimize a number of patches employed and attempts to provide maximal coverage of the individual events within the input sequence, the compressed representation comprising a discrete or continuous palette comprising a palette of sounds; wherein the epitome is trained by selecting an informed patch sampling from a training spectrogram, the informed patch sampling selected using an algorithm comprising: initializing P i (k) to uniform probability for all positions k in the training spectrogram; for n=1 where n is the number of patches, sampling a position t from P n , where: P n =spectrogram (: , t: t+patch_size); and for all positions k in the training spectrogram compute: Err(k)=sum(spec(:, t: t+patch_size)−P n )^ 2 ; P n+1 (k)=P n (k)*Err(k); and P n+1 (k)=P n+1 (k)/sum(P n+1 (k)); averaging each patch of the informed patch sampling to all possible offsets, T k , in the epitome weighted to the probability of observing an input sequence, Z k , given the current iteration of the epitome and particular offset (T k ) as a product of Gaussians over individual frequency-time values as: P ⁡ ( Z k ❘ T k , e ) = ∏ i ∈ S k ⁢ ⁢ N ⁡ ( z j , k ; μ T k ⁡ ( i ) , ϕ T k ⁡ ( i ) ) , where the i's are for the iteration over the individual frequency-time values of the training spectrogram; and a recognition component that utilizes, at least in part, the palette to construct a plurality of classifiers that facilitate recognition of a plurality of different classes in the audio environment input.