Uploaded March 2024 | Updated September 2026, 3 weeks ago

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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: github.com/deepset-ai/haystack-cookbook/blob/main/notebooks/using_speaker_diarization_with_assemblyai.ipynb

AssemblyAI-Haystack Integration docs: assemblyai.com/docs/integrations/haystack/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_mis_60

Blog post of this video: 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!

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