Implementing a Sound Identifier in Python
The talk will go over the journey of implementing a Shazam-style sound recogniser using DSP techniques and some fantastic libraries. It will cover implementation, challenges and further steps. The project is still a work in progress at the time of proposal and the code is available on GitHub. It was inspired by the Over-the-Air Audio Identification talk at FOSDEM 2016.
The basic structure of the project consists a classifier that fingerprints audio and stores it in a searchable form and a recogniser that fingerprints a smaller chunk of audio and then searches the stored records to find the most suitable fit for it. The recogniser will be exposed as an API to allow for different front-ends.
I will aim to introduce both the field of DSP and concepts behind applications like Shazam in a simple easy-to-understand manner. The audience will not need any prior experience in anything except Python.