Automatic Recognition of Events in Audio Data Using Supercomputer Cluster
Dangerous events automatic recognition by audio analysis employing parallel processing on a supercomputer cluster is described in the paper. Sound files recorded by microphones operating in a security surveillance system are processed by a sound event detection and classification algorithm. Because of the large amount of data, parallel computation is employed to speed up the analysis. The sound file recorded by the surveillance system is divided into chunks and processed by separate threads or processes. Several strategies for such parallel computation are introduced and discussed. Results obtained in tests using a supercomputer cluster are presented.
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is temporarily free for AES members.