Synthesis-Assisted Video Prototyping From a Document

Document Title

Synthesis-Assisted Video Prototyping From a Document

Document Information

• Subject Area: Human-Computer Interaction (HCI), Automated Video Creation
• Keywords: Video creation, video prototyping, virtual presenter, programming tutorials, voice narration, creative tools, tutorial automation

Research Background and Problem

• Identified Problems or Challenges:
  • Documents and videos differ in their educational presentation forms: documents are easy to scan and structurally clear, while videos are better suited for dynamic actions and voice support.
  • Creating high-quality explanatory videos requires scripting, refining scene content, recording, and post-editing, which poses significant production barriers for content creators lacking professional video production expertise.
  • Programming tutorials are often text-based and lack rich visual elements, making it challenging to create engaging instructional videos.
• Significance:
  • Instructional videos are a crucial medium for programming education. Automated tools for video creation supported by virtual presenters can lower the barrier for content creators, transforming complex information into visually guided content.
  • Automation can save time while improving video production quality.
• Research Motivation and Related Work:
  • Previous research has attempted to enhance tutorial presentation through segmented interactive video learning, video generation methods, and voice interfaces.
  • Unlike these efforts, this study focuses on directly generating interactive video prototypes with visual elements and virtual presenters from textual documents.

Solution

• Proposed Solution:
  • Doc2Video: An automated workflow tool for transforming textual documents into interactive video prototypes.
  • Core technologies include document parsing, script generation, text-to-speech (TTS) technology, virtual presenter video creation, and an interactive editing interface.
• Innovations:
  • Introduced an automated video generation prototype tool supporting virtual presenter video previews, capable of directly generating multiple instructional video scenes from structured documents.
  • The system features an interactive editing capability, allowing users to customize text, scene arrangement, and visual layouts.
• Implementation Steps and Key Technologies:
  1. Document Parser: Extracts the hierarchical structure of Markdown documents and annotates content components such as headings, paragraphs, code snippets, and images.
  2. Script Planner:
     • Converts document text into voice narration while matching visual materials and optimizing layout arrangements.
     • Provides functions such as scene merging and text highlighting to enhance script and content presentation.
  3. Video Synthesizer:
     • Uses TTS technology to generate voice segments and employs LipSync3D technology to create virtual presenter videos synchronized with the voice (including animated and real-person options).
  4. Interactive UI:
     • Enables users to edit narration content, adjust visual element layouts, and merge or split scenes in real-time.
• Technical Implementation Details:
  • Backend developed in C++ for document parsing and video synthesis; frontend based on web technologies to display dynamic layouts and user interactions.

Research Outcomes

• Specific Results:
  • Doc2Video successfully processed 65 open-source programming tutorials, generating 1,706 scenes, including 1,301 virtual presenter video segments, 488 code blocks, 410 text headings, and 565 highlighted keywords.
  • The average video duration was approximately 162 seconds, with visual and time estimation previews provided during initial generation.
• Experiments and User Feedback:
  • Experimental results show that the automatically generated scripts closely align with professional creators' workflows, and the video preview feature helps creators refine scripts more quickly.
  • Users indicated that editing functions (e.g., deleting paragraphs, highlighting keywords, switching layouts) are essential, and the tool significantly improved creation efficiency.
  • Six professional creators participated in user studies, and feedback consistently highlighted the tool's usefulness for both amateur and professional users.
• Advantages Compared to Existing Solutions:
  • Automatically generated scripts significantly reduce the initial workload of video production, offering higher efficiency compared to traditional manual design processes.
  • Provides virtual presenter video previews, enabling content creators to instantly verify the effectiveness of text and visual presentations.
• Limitations and Future Directions:
  • Limitations include inaccuracies in TTS technology for programming terminology, such as pronunciation errors.
  • Future directions include:
    • Developing language models to support tone adjustments.
    • Improving virtual presenter performance in specific application scenarios (e.g., emotional expression during code execution).
    • Supporting reverse generation from video to document.
    • Extending the method to other types of documents, such as descriptive content in non-technical domains.

Conclusion

This study proposes an automated tool, Doc2Video, for generating interactive video prototypes from programming documents, achieving promising results in experiments and receiving positive feedback from professional creators. The research contributes to lowering the barrier for video production, offering new tools for tutorial design and creation, while providing future research directions to enhance system functionality and adaptability.