Fast algorithms for high-order sparse linear prediction with applications to speech processing
Propose fast algorithms for sparse linear prediction. Usage of NlogN N log N algorithms for repeated solve of symmetric Toeplitz systems. Can handle even quite large dimensions and high-sampling rate. The fast algorithms shows possibilities for implementation in real-time systems. Experiments shows that high and low accuracy solutions performs almost equally well.
sparse linear prediction speech and audio processing linear programming real-time optimization speech reconstruction packet loss concealment