Explore the capabilities of OpenAI Whisper, the ultimate tool for audio transcription. In this video, we'll use Python, Whisper, and OpenAI's powerful GPT models to transcribe a Microsoft earnings call and then use the tool to summarize the call and determine its sentiment.
I'll take you step-by-step through the process of using Whisper for audio transcription and sentiment analysis and show you how it can save you time and improve accuracy. With Whisper, you can quickly and easily transcribe any audio file and analyze its sentiment using OpenAI's language models.
This video is a must-watch if you want to improve your audio transcription and sentiment analysis skills. Whether you're a data analyst, researcher, or just interested in the power of AI, you'll learn a lot from this demonstration of OpenAI Whisper. So, sit back, relax, and let's explore the amazing capabilities of OpenAI Whisper together!
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⏱️ Video Chapters
0:00 Intro
0:20 Getting Started with OpenAI Whisper
0:24 Installing OpenAI Whisper
0:44 OpenAI Whisper Model Types
1:01 Downloading Kaggle wav File
1:39 Transcribing Audio using model.transcribe
3:53 Detecting Audio Language using Mel Spectrogram
6:00 Earnings Call Mini Project
8:00 Transcribe Microsoft Earnings Call using OpenAI Whisper
8:51 Summarize Microsoft Earnings Whisper Transcription using OpenAI GPT-3
11:11 Analyze Sentiment of Whisper Transcriptions using OpenAI DaVinci Model
12:33 Create Sentiment Analysis Function
14:40 Visualize Whisper Transcription Sentiment using Seaborn
18:54 Outro
🏷️ Tags
#python
#openai
#whisper
#algotrading
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