Automatic Gender Detection Based on Characteristics of Vocal Folds for Mobile Healthcare System

<table class="table-group" id="tab5"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Dialect region</td><td class="align_center">Number of speakers (M + F)</td><td class="align_center">Accuracy</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">D2</td><td class="align_center">71 + 31</td><td class="align_center">94%</td></tr><tr><td class="align_left">D4</td><td class="align_center">69 + 31</td><td class="align_center">96%</td></tr><tr><td class="align_left">D5</td><td class="align_center">62 + 36</td><td class="align_center">96%</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr><tr class="table-fn"><td>M and F stand for male and female speakers, respectively.<br/></td></tr></table>

Results of gender detection by using all words simultaneously for all dialect regions.

Mobile Information Systems

tab5

Table 5

Table 5: Automatic Gender Detection Based on Characteristics of Vocal Folds for Mobile Healthcare System 