Maximum Phase Modeling for Sparse Linear Prediction of Speech
TABLE I: Relative improvement in sparsity (in %) over the speech signal, using the compared methods.
['[BOLD] Metrics', '[BOLD] Method', '[BOLD] LP2', '[BOLD] WLP2', '[BOLD] LP1']
It can be observed that the proposed MaxP method leads to a considerable increase of sparsity. This was reflected across 8 out of the 9 configurations (3 techniques and 3 metrics). However, for the unfavorable case (using the LP1-based techniques and the Gini index), a paired t-test revealed no significant differences, while all other results showed a statistically highly significant improvement (p<0.001). Finally it is worth noting that we did not observe any gender dependency through our experiments.