CLAIJan 11, 2025

PASS: Presentation Automation for Slide Generation and Speech

arXiv:2501.06497v28 citationsh-index: 3Has Code
Originality Incremental advance
AI Analysis

This addresses the time-consuming task of crafting presentations for professionals and educators, though it is incremental as it builds on existing document-to-slide automation by extending to general documents and adding delivery features.

The paper tackles the problem of automating presentation creation and delivery from general Word documents, introducing PASS, a pipeline that generates slides and provides AI-generated voice narration, with an LLM-based evaluation metric showing improvements in relevance, coherence, and redundancy.

In today's fast-paced world, effective presentations have become an essential tool for communication in both online and offline meetings. The crafting of a compelling presentation requires significant time and effort, from gathering key insights to designing slides that convey information clearly and concisely. However, despite the wealth of resources available, people often find themselves manually extracting crucial points, analyzing data, and organizing content in a way that ensures clarity and impact. Furthermore, a successful presentation goes beyond just the slides; it demands rehearsal and the ability to weave a captivating narrative to fully engage the audience. Although there has been some exploration of automating document-to-slide generation, existing research is largely centered on converting research papers. In addition, automation of the delivery of these presentations has yet to be addressed. We introduce PASS, a pipeline used to generate slides from general Word documents, going beyond just research papers, which also automates the oral delivery of the generated slides. PASS analyzes user documents to create a dynamic, engaging presentation with an AI-generated voice. Additionally, we developed an LLM-based evaluation metric to assess our pipeline across three critical dimensions of presentations: relevance, coherence, and redundancy. The data and codes are available at https://github.com/AggarwalTushar/PASS.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes