Variable-Length Source Dispersions Differ Under Maximum and Average Error Criteria

Acoustic Feature Transformation Combining Average and Maximum Classification Error Minimization Criteria

Acoustic feature transformation is widely used to reduce dimensionality and improve speech recognition performance. In this letter we focus on dimensionality reduction methods that minimize the average classification error. Unfortunately, minimization of the average classification error may cause considerable overlaps between distributions of some classes. To mitigate risks of considerable over...

Source and joint source-channel decoding of variable length codes

Several recent publications have shown that joint sourcechannel decoding (JSCD) could be a powerful technique for taking advantage of residual source redundancy. Furthermore, it appeared that the principle could also be successfully applied to variable length codes (VLCs). This paper gives an in-depth analysis of a new method recently proposed in [1], [2] to provide a low complexity soft decodi...

Constructions for Variable-Length Error-Correcting Codes

Optimised onstru tions for variable - length error

A Study of Variable Length Error Correcting Codes and Reversible Variable Length Codes: Analysis and Applications

is an authentic record of my work carried out under the supervision of Prof. N. Kalyanasundaram and Prof. Bhudev Sharma. I have not submitted this work elsewhere for any other degree or diploma. I am fully responsible for the contents of my Ph.D. Thesis. is a bonafide record of her original work carried out under our supervision. This work has not been submitted elsewhere for any other degree o...