Offered By: IBM
Easy Speech-to-Text with Python
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.
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Artificial Intelligence
288 EnrolledAt 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 audio file and detect the spoken language
- transcribe and translate an audio/YouTube file
What You'll Need
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. Remember that 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.
Estimated Effort
30 min
Level
Intermediate
Skills You Will Learn
Python, Data Science, Machine Learning, Data Analysis, Embeddable AI, PyTorch
Language
English
Instructors
Contributors
Joseph Santarcangelo
Senior Data Scientist at IBM
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
Read moreRoxanne Li
Data Scientist at IBM
I am an aspiring Data Scientist at IBM with extensive theoretical/academic, research, and work experience in different areas of Machine Learning, including Classification, Clustering, Computer Vision, NLP, and Generative AI. I've exploited Machine Learning to build data products for the P&C insurance industry in the past. I also recently became an instructor of the Unsupervised Machine Learning course by IBM on Coursera!
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