The Matrix Pencil and its Applications to Speech Processing
Abstract
Matrix Pencils facilitate the study of differential equations resulting from oscillating systems. Certain problems in linear ordinary differential equations, such as speech processing, can be represented as the problem of finding a canonical pencil strictly equivalent to a given pencil. It was originally applied by the radar community to phased array radar for signal directional finding applications. The Matrix Pencil (MP) algorithm is a direct data approach, and is a nonstochastic method. This approach has many benefits over a statistical approach. One benefit allows the user to approximate the error of the reconstructed signal without reconstructing the signal. Second, it takes less time and less computational power to execute the algorithm. Third, the matrix pencil approach has a lower variance of the estimates of the parameters of interest than a statistical approach such as traditional Linear Prediction Coding (LPC). Speech processing has many applications which directly assist in the advancement of technology. These technologies utilize speech tools that include, but are not limited to speech compression, speech enhancement, speech recovery, pitch estimation, and cochannel interference reduction. However, the speech processing community has not grasped the power of the MP algorithm, which will likely make a significant leap forward in improving these speech processing tools.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2007
- Accession Number
- ADA466668
Entities
People
- Andrew J. Noga
- Darren H. Haddad
Organizations
- Air Force Research Laboratory