.webp)
Efficiently navigating long-form content like podcasts, webinars, and tutorials can be challenging without proper structure. Generating chapters solves this problem by dividing content into logical sections, enabling better accessibility and usability. Sieve's Transcript Analysis Function simplifies this process with two powerful features: Chapter Generation and Custom Chapters.
In this post, we’ll explore how these modes work, why they are valuable, and provide a quick guide to implementing them.
Why Generating Chapters Matters
Generating chapters for content provides several benefits for both creators and consumers:
- Improved Navigation: Viewers can jump directly to sections of interest without manually scrubbing through the file.
- Enhanced Accessibility: Structuring content into chapters makes it more digestible and reduces cognitive overload.
- Increased Engagement: Clear segmentation encourages users to explore more of the content instead of abandoning it midway.
- Professional Presentation: Adding chapters demonstrates a polished, user-centric approach to content creation.
- SEO Benefits: Chapter markers can improve search rankings, particularly on platforms like YouTube.
By automating this process with Sieve’s Transcript Analysis Function, you can save time and effort while delivering high-quality results.
Overview of Sieve's Chapter Generation Features
Sieve's Transcript Analysis function offers two versatile modes for chapter creation:
1. Automated Chapters
This mode uses LLM-powered analysis to automatically segment your video or audio into logical chapters based on the transcript.
Ideal for:
- Long-form content with natural breaks
- Time-sensitive workflows
- Quick, reliable chapter generation without manual input
2. Custom Chapters
This mode provides greater control by letting you manually define chapter titles or use an LLM to generate them.
Best for:
- Projects requiring specific chapter names
- Marketing videos with branded messaging
- Content needing tailored chapter titles and timestamps
Available Modes:
- "Strict" Mode: Generates only the chapters specified in your custom chapter list
- "Extended" Mode (default): Combines your custom chapters with AI-generated ones for comprehensive coverage
Users can choose from various transcription backends like "groq-whisper" (default), "stable-ts," and "whisper-timestamped," as well as LLM backends including "gpt-4o-2024-08-06" (default), "gpt-4o-2024-05-13," and "gpt-4o-mini."
How to Generate Chapters Automatically?
Here’s a code snippet for automatically generating chapters from a video or audio file:
import sieve
file = sieve.File(url="https://storage.googleapis.com/sieve-prod-us-central1-public-file-upload-bucket/c4d968f5-f25a-412b-9102-5b6ab6dafcb4/52e169ed-9b30-4241-a956-591f2c6c30ab-chatgpt_tutorial_charlieChang.mp4")
transcription_backend = "groq-whisper"
llm_backend = "gpt-4o-2024-08-06"
transcript_analysis = sieve.function.get("sieve/transcript-analysis")
output = transcript_analysis.run(file,
transcription_backend,llm_backend, prompt="",
generate_summary=False, generate_title=False,
generate_tags=False, generate_chapters=True)
output_list = list(output)
for chapter in output_list[2]['chapters']:
print(f'{chapter['title']}:{chapter['timecode']} \n')Results
A Dance Tutorial
Ellen and Brian | JENNIE 'Mantra' Dance Tutorial
File Duration- 11:34
Time taken to generate chapters- 13s
| Chapters | Time-stamp |
|---|---|
| Introduction | 00:00 |
| Dance Tutorial Begins | 00:18 |
| Hand Movements | 00:34 |
| Adding Feet Movement | 01:39 |
| Combining Movements | 02:05 |
| Second Eight Count | 03:06 |
| Third Eight Count | 05:39 |
| Fourth Eight Count | 08:01 |
| Conclusion | 11:11 |
Comment: The "Conclusion" chapter is not an appropriate title and is not time-synced correctly. All other generated chapters are excellent.
A Technical Tutorial
Charlie Chang | ChatGPT Tutorial: How to Use Chat GPT For Beginners 2024
File Duration- 27:05
Time taken to generate chapters- 24s
| Chapters | Time stamp |
|---|---|
| Introduction | 00:00 |
| Account Setup | 00:59 |
| Limitations of ChatGPT | 01:53 |
| Basic Use of Prompts | 02:32 |
| Command Type 1: Facts | 02:34 |
| Command Type 2: Suggestions | 03:51 |
| Ad Break | 04:58 |
| Command Type 3: Language Translation | 05:26 |
| Command Type 4: Creative Writing | 09:33 |
| Command Type 5: Text Summarization | 14:23 |
| Command Type 6: List Generation | 15:43 |
| Command Type 7: Pros and Cons | 16:47 |
| Command Type 8: Studies and Quotes | 17:29 |
| Command Type 9: Feedback and Improvement | 18:40 |
| Command Type 10: Role Playing | 19:55 |
| Intro to ChatGPT & Demonstrations | 21:37 |
| Command Prompts for ChatGPT | 22:53 |
| Tips for Effective Use | 25:54 |
| Conclusion and Outro | 27:03 |
Comment: Excellent!
A Podcast
Lex Fridman Podcast | Aravind Srinivas: Perplexity CEO on Future of AI, Search & the Internet
File Duration- 3:02:15
Time taken to generate chapters- 2m 10s
| Chapters | Time-stamp |
|---|---|
| Exploring the Realms of Conversational AI: From Introduction and Concepts to Technical Insights and Functionality | 00:00:00 |
| Challenges and Strategies in AI, User Experience, and Product Design | 00:04:12 |
| Business Models & Market Dynamics | 00:09:13 |
| The Future of AI and Search Engines | 00:13:13 |
| User Experience Introduction and Considerations of Ad Breaks | 00:29:36 |
| Challenges in AI Output and Larry Page's Influence | 00:34:03 |
| Building a Product and Adapting to User Needs | 00:38:22 |
| Design Decisions | 00:43:03 |
| Influential Entrepreneurs: The Success of Bezos and Elon | 00:46:52 |
| The Impact of Open Source in AI and The Recipe for ChatGPT | 00:56:13 |
| Enhancing Post-Training Reasoning in Small Models with RLHF | 01:11:07 |
| Chain of Thought Reasoning | 01:16:06 |
| Future of AI Reasoning | 01:20:14 |
| The Intersection of Human Curiosity and AI: An Introduction to AI and Compute | 01:24:20 |
| AGI and Inference Limits | 01:32:23 |
| Ad Break | 01:36:38 |
| Perplexity and LLM Products | 01:41:21 |
| Challenges of Web Search Transformation | 01:52:32 |
| Exploring Truth and Prospects in AI Models and RAG | 01:56:25 |
| Improving Indexing and Snippets | 02:01:15 |
| Startup Challenges and Advice | 02:21:25 |
| Inspiration, Hard Work, and the Path to Education and Exploration | 02:28:26 |
| Ad Break, Search, and Knowledge Discovery: Navigating the Intersection of Marketing and Information Exploration | 02:32:00 |
| Perplexity and Curiosity | 02:36:19 |
| AI and Human Connection | 02:50:43 |
| Navigating the Intersection of AI and Human Values: Challenges, Biases, and Hope | 02:55:42 |
Comment: Excellent! Employed
min_chapter_length=210sparameter to control the number of chapters generated.
Real-World Use Cases
- Podcast Hosts: Segment episodes into topics for better listener retention and easier sharing of specific segments.
- Educators and Trainers: Enhance the learning experience by breaking down lectures into key concepts.
- Marketers and Creators: Highlight promotional content or product demonstrations for greater audience engagement
Why Choose Sieve for Chapter Generation?
- Efficient Automation: Generate accurate chapters instantly using advanced NLP and AI
- Flexible Customization: Tailor chapters with manual or AI-assisted input
- Multiple Backends: Choose from various transcription and LLM options
- Simple Interface: Generate chapters easily, regardless of technical expertise
Conclusion
Sieve's chapter generation capabilities streamline content organization while enhancing accessibility and engagement. Start using the Transcript Analysis Function today to transform how your audience interacts with your content.
For support or questions, join our Discord community or contact us at contact@sievedata.com.