Performance of the HGLER model on IEMOCAP.

<div><p>This research has proposed a new Emotion Recognition in Conversation (ERC) model known as Hierarchical Graph Learning for Emotion Recognition (HGLER), built to go beyond the existing approaches that find it difficult to request long-distance context and interaction across differe...

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Bibliographic Details
Main Author:	Qingping Zhou (1598803) (author)
Published:	2025
Subjects:	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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Performance of the HGLER model on IEMOCAP.

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