Towards Expressive Perception and Generation in Human-Computer Conversational Interaction

Towards Expressive Perception and Generation in Human-Computer Conversational Interaction
Author :
Publisher : Scientific Research Publishing, Inc. USA
Total Pages : 193
Release :
ISBN-10 : 9781649979551
ISBN-13 : 164997955X
Rating : 4/5 (55X Downloads)

Book Synopsis Towards Expressive Perception and Generation in Human-Computer Conversational Interaction by : Yaohua Bu

Download or read book Towards Expressive Perception and Generation in Human-Computer Conversational Interaction written by Yaohua Bu and published by Scientific Research Publishing, Inc. USA. This book was released on 2024-07-31 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: The construction of a natural interactive human-computer interaction has become an integral component of intelligent system development, constituting a core subject within the field of human-computer interaction. Grounded in the utilization of human perception theories, this study proposes a robust method for speech emotion recognition and a model for inferring user emotional state changes, thereby achieving a hu-man-computer interaction experience characterized by both listening and articulating, and conveying sentiments effectively. Simultaneously, focusing on the audio-visual modalities within human-computer interaction, this research explores methods for con-structing interactive feedback in auditory and visual modalities within real hu-man-computer dialog scenarios. This aims to synchronize textual, verbal, and visual expressions in human-computer interaction, enhancing its naturalness, improving user experience, and augmenting satisfaction and pleasure during interaction. The research contributions are as follows: Introducing a method that robustly identifies user emotional states in real hu-man-computer speech dialogue scenarios through the utilization of local and global attention mechanisms. This method generates robust and distinguishable representa-tions of speech emotion, thereby enhancing the robustness and accuracy of speech emotion recognition systems in authentic dialogue scenarios.


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