Loris for Your Cough

Roshan Mansinghani | Esmeralda Martinez | James McDougall | Travis McPhail
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Background
McAulay-Quatieri Method
Bandwidth Enhancement
Algorithm
   Loris Application
   Our Algorithm
Results
Conclusion
Poster
Group

Background

Our group brainstormed through many different project ideas.  After much deliberation, one of our group members told us of one of his performances with the Rice Choral Group.  It was a lovely performance and it was well received.  However, during the recording of the live performance, someone began to cough.  This was a tragic story, and we decided that being able to take out unwanted sounds from audio files would be a good idea for a project. 

We began to hash out ideas, and were first led to time domain analysis. Using pattern matching, we thought that we could find where the unwanted noise was in time, and remove it. However, how to remove the signal delicately enough to preserve the music was an item that required more analysis. Specifically, we then discussed Fourier analysis. We then thought we could analyze harmonics of the music, and look for anomalies throughout the spectrum. This, we believed, would provide limited functionality because, we would only be taking out noise maybe once in a sound file, and the rest of the time we would be removing musical instruments such as drums or cymbals.

Realizing that our noise would be a fairly unique event in the music, we began to discuss more sophisticated methods of analysis. Seeing how our problem was localized in time, we turned to short-time Fourier analysis. Research was then conducted into means of accomplishing short-time analysis.