Title :
Spectral distance measures for matching consecutive speech segments
Author_Institution :
ASELSAN Inc., Ankara, Turkey
Abstract :
In this study, spectral distance measures are compared for the task of matching consecutive speech segments. A new distance measure is proposed for this task, which decreases the error of the segment matching system from %16.6-22.1 to %9.8-12.5. A decision refinement algorithm based on pitch period estimation and LPC parameters is developed. The error of the system is reduced to %8.6-9.8 by using this algorithm.
Keywords :
estimation theory; speech processing; LPC parameter; consecutive speech segment matching; decision refinement algorithm; pitch period estimation; spectral distance measure; Measurement uncertainty; Mel frequency cepstral coefficient; Speech; Speech processing; Speech recognition; spectral distance; speech continuity measures; speech distance measures;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2013 21st
Conference_Location :
Haspolat
Print_ISBN :
978-1-4673-5562-9
Electronic_ISBN :
978-1-4673-5561-2
DOI :
10.1109/SIU.2013.6531351
