A Bayesian Approach to Estimation of Speaker Normalization Parameters
Table 2: Table illustrating the Vowel Recognition Performance using normalization in terms of Recognition Accuracy (RA) and its improvement over the baseline case
['[BOLD] Normalization Methods', '[BOLD] Hillenbrand Database  [BOLD] Recognition Accuracy (%)', '[BOLD] Hillenbrand Database  [BOLD] Improvement(%)', '[BOLD] Peterson & Barney Database  [BOLD] Recognition Accuracy (%)', '[BOLD] Peterson & Barney Database  [BOLD] Improvement(%)']
The recognition experiment on vowels can be divided into two categories, namely Gender Dependent Normalization: The recognition accuracies are shown using bar diagrams. In each Figure, there are three bar diagrams corresponding to different kinds of subject speakers. Each bar diagram comprises of three groups corresponding to different categories of reference speakers. The groups in turn contain 6 bars each, among which the first bar corresponds to baseline case and other bars correspond to various normalization methods. Gender Independent Normalization: In this experiment, normalization parameters for a speaker is computed by considering all other speakers present in the database (not of a particular gender) as reference speakers. The relative improvements in performance over the baseline case (without normalization) while using normalization, are indicated in a separate column. A negative entry in this column demonstrates a degradation in performance.