Title
Generalized analysis-by-synthesis based on system identification
Abstract
In this paper, we propose an approach to modify the input signal such that it can be coded more effectively within the generalized analysis-by-synthesis framework. Since most of the low-bit-rate speech coders are designed based on the human speech production mechanism, the perceived quality of the speech reconstructed in the decoder degrades seriously if the original input signal deviates from the pure speech. In order to alleviate this problem, we introduce a criterion which compromises the quantization error with the distortion incurred due to the modification. The coder-decoder (CODEC) characteristic is described in terms of a transfer matrix, and it is estimated according to the least squares criterion. In contrast to the conventional modification techniques, our approach can be implemented as a simple front-end for any analysis-by-synthesis type coders. The proposed approach is found effective in reducing audible distortions through a number of listening tests.
Year
DOI
Venue
2002
10.1109/ICASSP.2002.5743797
ICASSP
Keywords
Field
DocType
quantization error,analysis by synthesis,least square,speech,system identification,speech production,front end,transfer matrix
Speech processing,Speech coding,Computer science,Voice activity detection,Speech recognition,System identification,Quantization (signal processing),Distortion,Speech production,Codec
Conference
Volume
ISSN
ISBN
1
1520-6149
0-7803-7402-9
Citations 
PageRank 
References 
0
0.34
2
Authors
2
Name
Order
Citations
PageRank
Nam Soo Kim127529.16
Joon-Hyuk Chang2162.13