Feature Aggregation with Two-Layer Ensemble Framework for Multilingual Speech Emotion Recognition

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left">Corpus</td><td class="align_center">Language</td><td class="align_center">Number of original samples</td><td class="align_center">Number of preprocessed samples</td><td class="align_center">Number of features</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">IEMOCAP</td><td class="align_center">English</td><td class="align_center">10,039</td><td class="align_center">8,000</td><td class="align_center">200</td></tr><tr><td class="align_left">KETI</td><td class="align_center">Korean</td><td class="align_center">19,374</td><td class="align_center">8,000</td><td class="align_center">200</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Comparison of original sample count and preprocessed sample count with extracted features.</div>

Mathematical Problems in Engineering

tab2

Table 2

Table 2: Feature Aggregation with Two-Layer Ensemble Framework for Multilingual Speech Emotion Recognition 