Which algorithm should I use for signal (sound) one class classification?

Question

Update this question was previously titled as \"Give me the name of a simple algorithm for signal(sound) pattern detection\"

1. My o

Answer 1

A Naive Bayes Classifier may be worthwhile here, classifying sound samples into ones which contain your species of interest and ones which do not. It works quite well for complex phenomena; I once used it to decide if a given millimeter-wave RADAR data set contained an obstacle such as brush, a tank trap, etc. As for how to break up your continuous data into discrete chunks for the Bayesian classifier, you might just slide along the continuous data set and break off chunks equal in length to your insect sample. For example, if the sample you're comparing against is 2 seconds long, you might feed the discriminator 0-2s, 0.5-2.5s, 1-3s, etc. You'll need to train the discriminator, but that is a common requirement of any machine learning-based solution.

These sorts of approaches are about the only way to go if your insect species doesn't have a single, relatively distinct sound that you're looking for. Cross-correlation/convolution are of limited utility if you're looking for something more complex than a single sound which may be at higher or lower volume.

There are naive Bayes classifier implementations for several languages, such as nbc.