Baby Cry Sound detection
Since you have frequency bucket information, you essentially have a frequency histogram.

If you treat histograms as n dimensional vectors, you can use dot product to get a similarity value that goes from 0 to 1 and could tune that so that sounds that have a value greater than say 0.6 are considered a match.

For more information check this out:  http://blog.demofox.org/2015/02/13/writing-a-basic-search-engine-aka-calculating-similarity-of-histograms-with-dot-product/

Alternately you could get a little more advanced and use support vector machines, which require training data of both negatives and positives to find a way to differentiate hits and misses.