How to classify a data as not matching any label
Let's phrase it another way, decomposing into two problems:


given a sound, we want to know if it's of class A
given a sound, we want to know if it's of class B


This way of putting it is valuable to some techniques, notably "one-class classification" and "PU learning" (learning from positive and unlabeled examples). These techniques are very relevant when you want to know "does my item follow a given distribution D?", which is exactly what you're looking for.

Still, if you have (or can collect) a lot of data that is neither A nor B, you may simply label it as a garbage class C and use a common classifier - however, it may actually be harmful, because you're likely assuming wrong things about class C [Li, Liu and Ng, "Negative Training Data can be Harmful to Text Classification", 2010]. It could work and is much simpler to develop, may be good enough depending on your case.