Princeton University Library Catalog
- Smith, Matthew Clarence [Browse]
- Senior thesis
- Engelhardt, Barbara [Browse]
- McConnell, Mark [Browse]
- Princeton University. Department of Mathematics [Browse]
- Class year:
- 31 pages
- Summary note:
- In this paper, we demonstrate a method by which music can be automatically transcribed from audio using feed-forward neural networks. That is, given an audio recording containing multiple instruments, a computer can automatically output the pitch and rhythm information for each instrument's part so that it could be written using
standard musical staff notation. We approach this in two steps: First, we use a neural
network to separate the composite audio file into separate audio files for each instrument. Then, using those, we utilize a second neural network to perform pitch detection.
From that result, we can finally determine the timing for each note empirically. This
is then sufficient to notate each instrument's part. We present our results, and discuss
the successes and shortcomings of this approach.