A Robust Method for Speech Emotion Recognition Based on Infinite Student’s <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2725pt" id="M1" height="10.5867pt" version="1.1" viewBox="-0.0657574 -10.3142 6.00502 10.5867" width="6.00502pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-117" d="M324 430H196L233 583L223 592L145 529L120 430H54L29 396L31 388H111L56 126C33 15 54 -12 77 -12C137 -12 214 57 250 95L233 119C208 92 155 59 138 59C126 59 120 70 131 125L186 390L298 394L324 430Z"/><glyph.data ascent="3473" descent="-2876" horiz-adv-x="341" vert-adv-y="341"/></g></svg>-Mixture Model

<div>Comparison of SER accuracy between the iSMM and GMM classifiers on five emotions of the Aibo.</div>

Mathematical Problems in Engineering

fig7

Figure 7

Figure 7: A Robust Method for Speech Emotion Recognition Based on Infinite Student’s <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2725pt" id="M1" height="10.5867pt" version="1.1" viewBox="-0.0657574 -10.3142 6.00502 10.5867" width="6.00502pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-117" d="M324 430H196L233 583L223 592L145 529L120 430H54L29 396L31 388H111L56 126C33 15 54 -12 77 -12C137 -12 214 57 250 95L233 119C208 92 155 59 138 59C126 59 120 70 131 125L186 390L298 394L324 430Z"/><glyph.data ascent="3473" descent="-2876" horiz-adv-x="341" vert-adv-y="341"/></g></svg>-Mixture Model 

Mathematical Problems in Engineering

A Robust Method for Speech Emotion Recognition Based on Infinite Student’s -Mixture Model

Figure 7