PASS: Presentation Automation for Slide Generation and Speech
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Abstract (arXiv)
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.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 8 of its 15 references that are in the map. First posted on arXiv 11 Jan 2025.
Builds on
8 of 15 references.
References · 8
- 2024The Llama 3 Herd of Modelscited by 14,715
- 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276
- 2017Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictionscited by 804
- 2021SpeechBrain: A General-Purpose Speech Toolkitcited by 406
- 2021DOC2PPT: Automatic Presentation Slides Generation from Scientific Documentscited by 70
- 2021D2S: Document-to-Slide Generation Via Query-Based Text Summarizationcited by 50
- 2024Enhancing Presentation Slide Generation by LLMs with a Multi-Staged End-to-End Approachcited by 17
- 2024Robustness of Structured Data Extraction from In-plane Rotated Documents using Multi-Modal Large Language Models (LLM)cited by 7
Built on by
Citing papers per year: 2025: 3; 2026: 4.
7 papers.
- 2026AI for Auto-Research: Roadmap & User Guidecited by 11
- 2025PresentCoach: Dual-Agent Presentation Coaching through Exemplars and Interactive Feedbackcited by 5
- 2025Generating Narrated Lecture Videos from Slides with Synchronized Highlightscited by 4
- 2025VideoAgent: Personalized Synthesis of Scientific Videoscited by 3
- 2026AI-Generated Slides: Are They Good? Can Students Tell?cited by 0
- 2026DeepSlide: From Artifacts to Presentation Deliverycited by 0
- 2026Lect=uraAgents: A Multi-Agent Framework for Adaptive Personalized AI-Assisted Learning and Embodied Teachingcited by 0
- 2026Lect=uraAgents: A Multi-Agent Framework for Adaptive Personalized AI-Assisted Learning and Embodied Teaching15 Jun 2026
- 2026AI for Auto-Research: Roadmap & User Guide18 May 2026
- 2026AI-Generated Slides: Are They Good? Can Students Tell?13 May 2026
- 2026DeepSlide: From Artifacts to Presentation Delivery1 Apr 2026
- 2025PresentCoach: Dual-Agent Presentation Coaching through Exemplars and Interactive Feedback19 Nov 2025
- 2025VideoAgent: Personalized Synthesis of Scientific Videos14 Sep 2025
- 2025Generating Narrated Lecture Videos from Slides with Synchronized Highlights5 May 2025