Get AssemblyAI API key for this tutorial: https://www.assemblyai.com/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_mis_60 LLMs work wonders on text data but if you want to use audio or video files instead of text, things get a bit trickier. An easy solution is to transcribe the audio or video files. This would work but you will lose valuable information, especially in multi-speaker situations, like how many people were speaking and who said what. In this video, we’ll learn how to build a RAG application in 10 minutes that can take multiple speakers into account when answering a question. Colab notebook: https://github.com/deepset-ai/haystack-cookbook/blob/main/notebooks/using_speaker_diarization_with_assemblyai.ipynb AssemblyAI-Haystack Integration docs: https://www.assemblyai.com/docs/integrations/haystack/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_mis_60 Blog post of this video: https://haystack.deepset.ai/blog/level-up-rag-with-speaker-diarization 00:00 Introduction 00:32 Effect of Speaker Labels 01:49 Libraries and example files 04:43 Transcription Pipeline 07:52 RAG Application 10:34 Results 11:52 Try it out yourself! ▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT ▬▬▬▬▬▬▬▬▬▬▬▬ 🖥️ Website: https://www.assemblyai.com/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_mis_60 🐦 Twitter: https://twitter.com/AssemblyAI 🦾 Discord: https://discord.gg/Cd8MyVJAXd ▶️ Subscribe: null 🔥 We're hiring! Check our open roles: https://www.assemblyai.com/careers ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #MachineLearning #DeepLearning