Robust parameters for automatic segmentation of speech
A. K. V. SaiJayram, Viswanathan Ramasubramanian, T.V. Sreenivas · IEEE International Conference on Acoustics Speech and Signal Processing · 2002
Automatic segmentation of speech is an important problem that is useful in speech recognition, synthesis and coding. We explore in this paper, the robust parameter set, weighting function and distance measure for reliable segmentation of noisy speech. It is found that the MFCC parameters, successful in speech recognition. holds the best promise for robust segmentation also. We also explored a variety of symmetric and asymmetric weighting lifters. from which it is found that a symmetric lifter of the form 1 + A sin1/2(πn/L), 0 ≤ n ≤ L − 1, for MFCC dimension L, is most effective. With regard to distance measure, the direct L2norm is found adequate.