The goal of this project is to use HPCC Systems technology to help build a reliable classification model that is able to accurately classify an input sound file to a description of its location. The project intends to not only demonstrate a proof of concept for this technology but also to lay the groundwork for what could be the next step in forensic audio analysis and a new means of gathering information through sound.
In digital signal processing there are things called Impulse Responses (IRs) that are often used to capture and recreate the audio characteristics of a certain space or piece of equipment. Simply put the audio characteristics of any room can be described as an equation or a system that takes an input sound and then transforms it. An IR is essentially the result of putting a very short burst of sound, or an impulse, into this system and recording the response. We can then take this IR and use it to transform other sounds, making it seem as if they were recorded in the same room.
Using this principle it is possible to create a huge amount of audio data from a few impulse responses and some dry samples which we can then use to train a neural net as a classifier.