Extracting phone call insights is useful for many applications, like quality assurance, call centers, sales coaching, and more. In this tutorial, we'll learn how to extract phone calls automatically with LLMs and Python. We'll use the framework LeMUR to automatically summarize a phone inquiry at a home building company, as well as extract action items to follow up on and contact information to get back in touch with the caller. Relevant links: 1. Get an AssemblyAI API Key: https://www.assemblyai.com/dashboard/signup?utm_source=youtube&utm_medium=referral&utm_campaign=yt_ry_6 2. GitHub repo: https://github.com/AssemblyAI-Examples/extract-call-insights 3. Blog post: https://www.assemblyai.com/blog/extract-call-insights-llms-python/ 4. AI-powered call analytics: https://www.assemblyai.com/blog/ai-powered-call-analytics-how-to-extract-insights-customer-conversations/ ▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT ▬▬▬▬▬▬▬▬▬▬▬▬ 🖥️ Website: https://www.assemblyai.com/discover/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_ry_6 🐦 Twitter: https://twitter.com/AssemblyAI 🦾 Discord: https://discord.gg/Cd8MyVJAXd ▶️ Subscribe: null 🔥 We're hiring! Check our open roles: https://www.assemblyai.com/careers ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 0:00 Result preview 0:25 Repo and blog 0:35 Setup 1:05 Writing the program 1:55 LeMUR 2:10 Writing the LLM prompt 3:26 Prompting the LLM 4:00 Extracted call insights 4:24 Extracted information verification 5:01 Use cases 5:16 4 LLM frameworks to build AI apps with audio data #MachineLearning #DeepLearning