DocumentCode :
2270751
Title :
Memory and complexity reduction for inventory-style speech enhancement systems
Author :
Nickel, Robert M. ; Martin, Rainer
Author_Institution :
Dept. of Electr. Eng., Bucknell Univ., Lewisburg, PA, USA
fYear :
2011
fDate :
Aug. 29 2011-Sept. 2 2011
Firstpage :
196
Lastpage :
200
Abstract :
In this paper we are presenting a method that provides a dramatic reduction in memory requirement and computational complexity for an inventory-style speech enhancement scheme with only a small impact on the perceptual quality of the output of the system. Inventory-style or corpus-based speech enhancement generally attempts to generate a clean speech signal from a noisy speech signal by first estimating the characteristics of the underlying clean signal and then recreating it via corpus-based speech synthesis. As such, inventory-based enhancement is very different from most traditional methods which are typically relying on adaptive filtering or spectral subtraction. The advantage of inventory-based enhancement is its (principal) ability to deliver a very natural sounding output. A significant drawback is its large memory requirement and its large computational complexity (in comparison to traditional techniques)1. The method proposed in this paper allows for a flexible reduction of the memory requirement as a function of the desired perceptual quality of the output. A data reduction by almost factor 10 is achievable with only minor losses in perceptual quality. Furthermore, a significant reduction of computational complexity is a possible choice in the implementation of the procedure.
Keywords :
computational complexity; data reduction; speech enhancement; speech synthesis; adaptive filtering; computational complexity reduction; corpus-based speech enhancement; corpus-based speech synthesis; data reduction; inventory-style speech enhancement system; memory reduction; natural sounding; spectral subtraction; speech signal generation; Complexity theory; Data compression; Memory management; Signal to noise ratio; Speech; Speech enhancement; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2011 19th European
Conference_Location :
Barcelona
ISSN :
2076-1465
Type :
conf
Filename :
7074152
Link To Document :
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