TY - GEN
T1 - Re-estimation of linear predictive parameters in sparse linear prediction
AU - Giacobello, Daniele
AU - Murthi, Manohar N.
AU - Christensen, Mads Græsbøll
AU - Jensen, Søren Holdt
AU - Moonen, Marc
PY - 2009
Y1 - 2009
N2 - In this work, we propose a novel scheme to re-estimate the linear predictive parameters in sparse speech coding. The idea is to estimate the optimal truncated impulse response that creates the given sparse coded residual without distortion. An all-pole approximation of this impulse response is then found using a least square approximation. The all-pole approximation is a stable linear predictor that allows a more efficient reconstruction of the segment of speech. The effectiveness of the algorithm is proved in the experimental analysis.
AB - In this work, we propose a novel scheme to re-estimate the linear predictive parameters in sparse speech coding. The idea is to estimate the optimal truncated impulse response that creates the given sparse coded residual without distortion. An all-pole approximation of this impulse response is then found using a least square approximation. The all-pole approximation is a stable linear predictor that allows a more efficient reconstruction of the segment of speech. The effectiveness of the algorithm is proved in the experimental analysis.
UR - http://www.scopus.com/inward/record.url?scp=77953835048&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77953835048&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2009.5470202
DO - 10.1109/ACSSC.2009.5470202
M3 - Conference contribution
AN - SCOPUS:77953835048
SN - 9781424458271
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1770
EP - 1773
BT - Conference Record - 43rd Asilomar Conference on Signals, Systems and Computers
T2 - 43rd Asilomar Conference on Signals, Systems and Computers
Y2 - 1 November 2009 through 4 November 2009
ER -