Transform Podcasts into Text with IBM Granite 3.3 & watsonx.ai!

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Discover how to convert spoken content into written form using IBM's latest AI Speech Model. In this tutorial, you'll learn to transcribe a podcast from YouTube using the open-source IBM Granite 3.3 speech model and summarize it with the Granite-3.3-8B-Instruct large language model (LLM) within a watsonx.ai notebook.

What You'll Learn:

— Setting up your environment using the Jupyter Notebook
— Installing and importing necessary libraries like torchaudio, moviepy, and transformers
— Downloading and processing podcast audio from YouTube
— Converting audio files for model inference and generating transcripts using Granite-speech-3.3-8b
— Summarizing transcripts using the Granite instruct model

Whether you're an AI enthusiast, developer, or researcher, this tutorial equips you with the tools to enhance your AI models' capabilities in processing and summarizing audio content.

🔗 Check out the full tutorial here: https://www.ibm.com/think/tutorials/automatic-speech-recognition-podcast-transcript-granite-watsonx-ai

🔗 Check out the Github notebook: https://github.com/IBM/ibmdotcom-tutorials/blob/main/generative-ai/granite-speech-3.3-8b.ipynb

🔗 Check out the models here:
https://huggingface.co/ibm-granite/granite-speech-3.3-8b
https://huggingface.co/ibm-granite/granite-3.3-8b-instruct


For more technical tutorials, articles, and learning resources, check out IBM Developer: https://ibm.biz/ibm-developer-yt

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