A Multimodal Framework Bridging Classical Thought and Artificial Intelligence for the Digital Preservation and Cross-Cultural Dissemination of the Tao Te Ching

This study presents a comprehensive, multimodal approach to exploring and disseminating the Tao Te Ching, a foundational text of classical Chinese philosophy. Recognizing the global significance of this work and the limitations of existing translation and speech synthesis tools, we constructed a high-quality trilingual corpus comprising the original Ancient Chinese text, modern Chinese annotations, and authoritative English translations. This corpus served as the basis for generating both synthetic and real human voice datasets using Neural Text-to-Speech technologies and professional voice recordings, respectively. We systematically introduced regional accent diversity and applied rigorous segmentation standards to enhance the dataset's linguistic variety and processing efficiency. To evaluate the speech quality of AI-generated content, we used the Non-Intrusive Speech Quality Assessment (NISQA) framework and the OpenAI Whisper model, respectively. The results showed that both standard and non-standard accented speech were highly natural and intelligible, but we encountered greater difficulties when processing artificially recorded speech. The findings demonstrate the effectiveness of combining large language models with curated textual and speech resources for advancing cross-cultural communication, preserving classical knowledge, and fine-tuning AI systems for multimodal tasks such as semantic modeling and speech synthesis. This research not only bridges ancient wisdom with modern AI technology but also establishes a replicable framework for digital humanities studies in multilingual and multicultural contexts.