Impact of different components of graph modules on the performance of proposed HGLER on IEMOCAP and MELD.

Impact of different components of graph modules on the performance of proposed HGLER on IEMOCAP and MELD.

<p>Impact of different components of graph modules on the performance of proposed HGLER on IEMOCAP and MELD.</p>

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Qingping Zhou (1598803) (author)
منشور في:	2025
الموضوعات:	Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified make things consistent enhance emotional understanding 68 %, surpassing enhancing emotional comprehension preprocessing methods common using hierarchical graph new emotion recognition model also showed hgler ), built data yet tracking hierarchical graph learning conversations </ p hierarchical graph emotion recognition enhancing learning graph system traditional methods based learning art methods xlink "> various types various parts understand emotions testing informed systems dealing superb performance slight changes several forms set aside results validate request long previous works one aimed model stability model known many varieties hgler uses hgler model handling conversations go beyond fold manner findings demonstrate existing approaches distance context 28 %;
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