In this paper, we use mathematical tools developed for chaos theory and time series analysis and apply them to the analysis and resynthesis of musical instruments. In particular, we can embed a basic one-dimensional audio signal time series within a higher-dimensional space to uncover the underlying generative attractor. Röbel (1999, 2001) described a neural-net model for audio sound synthesis based on attractor reconstruction. We present a different methodology inspired by Kaplan and Glass (1995) to resynthesize the signal based on time-lag embedding in different numbers of dimensions, and suggest techniques for choosing the approximate embedding dimension to optimize the quality of the synthesized audio.

Authors: Knopke, Ian; Nichols, Eric
Affiliation: Indiana University
AES Conference: 31st International Conference: New Directions in High Resolution Audio (June 2007)
Paper Number: 14
Publication Date: June 1, 2007
Subject: High Resolution Audio

Click to purchase paper as a non-member or you can login as an AES member to see more options.

No AES members have commented on this paper yet.

Subscribe to this discussion

To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.

Start a discussion!

If you would like to start a discussion about this paper and are an AES member then you can login here:
Username:
Password:

If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.