Easy Speech-to-Text with Python
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Learn how to implement easy and accurate speech-to-text systems using Python. Explore libraries and techniques for converting audio into text for real-time transcription applications.
At a Glance
This project explores the multilingual automatic speech recognition (ASR) system and the architecture of signal processing using Python. Today, ASR systems are available through multiple sources, including IBM Watson® Speech to Text, and some publicly available systems through Open AI.
Why you should do this guided project?
A look at the project ahead
- Understand how signal processing works.
- Load an audio file and detect the spoken language.
- Transcribe and translate an audio or YouTube file.
Prerequisites
Everything else is provided to you via the IBM Skills Network Labs environment, where you will have access to the Cloud IDE and Python runtimes that we offer as part of the IBM Skills Network Labs environment. The IBM Skills Network Labs environment comes with many things pre-installed (e.g., Docker) to save them the hassle of setting everything up. Also, note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.
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