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1
OpenAI's Whisper
2
Idea Behind Better Search
3
Downloading Audio for Whisper
4
Download YouTube Videos with Python
5
Speech-to-Text with OpenAI Whisper
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Hugging Face Datasets and Preprocessing
7
Using a Sentence Transformer
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Initializing a Vector Database
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Build Embeddings and Vector Index
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Asking Questions
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Hugging Face Ask YouTube App
Description:
Learn how to enhance YouTube search functionality using OpenAI's Whisper, a state-of-the-art speech-to-text model. Explore the concept of improved search capabilities and build a solution using Whisper, transformers, and vector search. Discover how to download YouTube videos, transcribe audio, create sentence embeddings, and implement scalable vector search. Gain hands-on experience with tools like pytube, Sentence transformers, Pinecone vector database, Streamlit, and Hugging Face spaces. Follow along to create a more efficient YouTube search experience that allows users to find specific, concise answers within lengthy videos.

How to Use OpenAI Whisper to Fix YouTube Search

James Briggs
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