Guitars can be tuned to a a variety of tunings. This is especially common in certain genres of music, notably folk music and heavy metal, for example.

The basic idea here is to take recordings on music played in known guitar tunings. I have database of known songs in know tunings by a variety of artists and have the associated recordings.

A deep learning system can then be trained with input samples (many short snippets from every recording) and trained to classify the tunings. New music can then be inputted to determine the guitar tuning.

A variety of interesting questions need to researched: * What the the best format for the input audio * What type and configuration of network is best * How to format the class labels: A n-class classifier could be trained, or a classifier could be trained to assign a tuning to each string.