Filter the audio using scipy's filtering module here.

There are a number of different methods for this, but I'm going to assume that what you want is something that will work well without being incredibly difficult to implement. The first step is to eliminate background noise.

Just as it would be acquired from a microphone. I've done quite a bit of this stuff for large scale data science, and while I can't comment on exactly how proprietary programs do it, I can comment on how it's done in academia and provide a solution that is straightforward and will give you the power and flexibility that you want for this approach.įirstly: Assuming that what you have is some chunk of audio without any filtering done on it. The problem here is to take a number of slightly different pronunciations and get some kind of meaningful distance between them. The problem in speech recognition is resolving many similar pronunciations to the same representation.

The specific algorithms used by speech-recognition in fact are nearly the opposite of what you would like to use here. A lot of people seem to be suggesting some sort of edit distance, which IMO is a totally wrong approach for determining the similarity of two speech patterns, especially for patterns as short as OP is implying.

Ocenaudio compare