Rapid UI Prototyping with Python Streamlit: Audio Transcription, End-to-End
Podcasts, video calls, and voice calls produces hours of speech every day. Turning that speech into text is now routine for meetings, customer-support calls, and more. A simple audio to text tool can help us capture conversations on meetings, phone or our smart watch - once recorded we can transcribe it and give it to things like chatgpt for all the wonderful insights possible. This project demonstrates how quickly we can build ready to use tools using Streamlit. As a showcase, we built an AI-powered Audio Transcription Tool that uses speech recognition models to convert audio into text with high accuracy. The app addresses a common limitation we found in nearly every transcription tool we evaluated — strict limits on audio length or file size, which made them impractical for long conversations.
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We've open-sourced this project for you all to try out: https://github.com/kubenine/Audio-to-text
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