In the evolving landscape of customer service within the digital economy, traditional methods of service quality assessment have shown significant limitations, this research proposes a novel deep-learning approach to service quality assessment, focusing on the Vietnamese service sector. By leveraging a multi-modal pipeline that transcends traditional evaluation methods, the research addresses the limitations of conventional assessments by analyzing speech, speaker interactions and emotional content, offering a more comprehensive and objective means of understanding customer service interactions. This aims to provide organizations with a sophisticated tool for evaluating and improving service quality in the digital economy.

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