Construction and Empirical Study of a Quality Evaluation Model for AI-Driven Multimodal Language Services
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Abstract
The language service industry in China is experiencing increasingly vigorous development and facing unprecedented opportunities for growth, driven in part by the rising need for accurate translation and multimodal processing of technical specifications, simulation reports, and global communication materials in advanced engineering fields such as electromagnetic waves, antennas, and propagation. This paper aims to construct an evaluation model for assessing the quality of AI-driven multimodal language services. First, through a comprehensive review of existing literature, this study identifies the key dimensions influencing multimodal language service quality and selects appropriate quality evaluation methods. Data are collected through questionnaires, and the Fuzzy Comprehensive Evaluation method is used to conduct an empirical assessment of the platform’s service quality, in order to verify the feasibility and effectiveness of the constructed evaluation model. The research results show that the evaluation model can objectively and accurately reflect the quality level of AI-driven multimodal language services, with accuracy and user satisfaction being the core factors affecting service quality. This study can provide theoretical references and practical guidance for multimodal language service providers to optimize service quality and enhance user experience, particularly benefiting service scenarios that involve specialized terminology, technical diagrams, and cross-language communication requirements in electromagnetic engineering applications.
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