979-8-3315-3297-0/25/$31.00 ©2025 IEEE An AI-Driven Workflow for Preserving Traditional Malay Music Videos: A Case Study in Cultural Heritage Enhancement *Note: Sub-titles are not captured in Xplore and should not be used M.Izani Applied Media Department Higher Colleges of Technology Abu Dhabi, UAE mohamadizanizainal@gmail.com K. Trinh Applied Media Department Higher Colleges of Technology Abu Dhabi, UAE ktrinh@hct.ac.ae M. Gabr Applied Media Department Higher Colleges of Technology Abu Dhabi, UAE mgabr@hct.ac.ae A. Kaleel Applied Media Department Higher Colleges of Technology Abu Dhabi, UAE akaleel@hct.ac.ae H. Harumaini Sultan Salahuddin Abdul Aziz Shah Polytechnic Selangor, Malaysia hazlina@psa.edu.my A. Assad Applied Media Department Higher Colleges of Technology Abu Dhabi, UAE aali3@hct.ac.ae Abstract— Preserving cultural heritage like traditional arts and traditional music becomes increasingly challenging during the digital age. We presented a workflow that uses generative AI to preserve traditional Malay music in video format with an emphasis on cultural integrity through photorealistic video generation. Our enhanced framework uses Low-Rank Adaptation (LoRA) combined with Splitter.ai-based vocal isolation and Kling.ai motion synchronization along with other artificial intelligence techniques to completely process and enhance audiovisual elements. We started our research design by deploying generative AI tools throughout a production process starting from concept development, facial synthesis, and training alongside motion-lip synchronization before post- production to ensure visual harmony without sacrificing storytelling elements and technical precision. The workflow consists of expert validation points, loop refinement linked to cultural accuracy loss, and computational performance. The end results show that generative AI techniques create successful links between traditional artistic forms with the present multimedia formats to preserve traditional Malay music. This research introduces a workflow that allows reproducible AI- assisted preservation methods which give opportunities to heritage experts and authorities helpful guidance to integrate technical innovations with cultural integrity. Keywords—Artificial Intelligence, Cultural Heritage, AI- Driven Video Production, LoRA Face Cloning, AI Audio Processing, Motion Synchronization, Intangible Cultural Heritage (ICH) I. INTRODUCTION The attention on intangible cultural heritage preservation has grown in recent years because traditional arts face vulnerability alongside cultural dangers [1]. Traditional music is one of the arts that faces high risks of disappearance when globalization affects how people consume media because this music media is closely linked to people's heritage and community traditions [2]. The integration of artificial intelligence (AI) technology has become a promising approach for cultural preservation because of existing issues in the field [3]. Implementing generative AI for traditional audiovisual materials is very challenging and difficult because they need precise execution alignment as well as accurate cultural authenticity and thematic coherence [4]. The existing literature examines immersive video [5], facial animation [6], or generative image synthesis [7] independently while failing to develop an integrated system that verifies cultural content and narrative coherence. The proposed workflow presents a complete AI process to transform traditional Malay music videos while preserving cultural heritage while defining clear narrative structures. This method uses the generative tools Tensor for face cloning together with Splitter.ai for audio track separation and Kling.ai for motion and lip-sync alignment while Adobe Premiere Pro’s AI-enhanced editing suite delivers the complete workflow that avoids new data collection processes. The final framework verifies visual- musical match while embracing Malay heritage themes to provide adjustable representations of this intangible cultural expression. Our workflow deploys artificial intelligence processes to preserve traditional Malay music artifacts through face cloning technology followed by motion-lip synchronization and audio-visual compositing methods in order to generate effective cultural restorations. The evaluation system combines expert judges with precision synchronization measurements to create an evidence-based method for determining cultural accuracy during AI-assisted conservation processes. The presented methodology creates digital heritage preservation methods which are easily repeatable with cultural sensitivity. This study builds a potential benchmark for future AI-based ICH revitalization research by integrating AI technologies into an integrated process. The research model would benefit different stakeholders including practitioners, policymakers and local communities through its validated framework to preserve traditional cultural expressions. II. LITERATURE REVIEW Intangible cultural heritage (ICH) encompassing oral traditions, performing arts, and indigenous knowledge underpins community identity across the globe [8, 9]. Yet, unlike material artifacts, ICH remains vulnerable to erosion in an increasingly globalized media environment [10, 11]. UNESCO’s Convention for the Safeguarding of the Intangible Cultural Heritage has propelled preservation initiatives by promoting systematic documentation and intergenerational 2025 5th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET) | 979-8-3315-3297-0/25/$31.00 ©2025 IEEE | DOI: 10.1109/IRASET64571.2025.11008319 Authorized licensed use limited to: Higher College of Technology. Downloaded on June 02,2025 at 10:09:00 UTC from IEEE Xplore. Restrictions apply.