Unlocking Speech Recognition: Deep Learning in Acoustics

Explore the techniques of AI communication by developing speech-to-text models using TensorFlow and PyTorch. This course will teach you the essential techniques to build advanced speech-to-text models, turning spoken words into actionable commands.

Speech recognition technology offers seamless communication between users and digital responses. Accurately processing speech requires an understanding of technical complexities and natural variation. In this course, Unlocking Speech Recognition: Deep Learning in Acoustics, you’ll gain the ability to develop sophisticated speech-to-text models that can accurately interpret human speech and respond appropriately. First, you’ll explore the basics of sound data and feature extraction, gaining an understanding of how to process and prepare audio signals for analysis. Next, you’ll discover the process of designing and training robust speech recognition models, employing cutting-edge neural networks to capture the nuances of human speech. Finally, you’ll learn how to enhance your model's accuracy by tackling common challenges such as background noise and varying accents. When you’re finished with this course, you’ll have the skills and knowledge of speech recognition technology needed to implement effective speech-to-text systems, which will lead to more natural human-device interactions.

• Course Overview 1min
• Foundations of Sound Data and Speech Recognition 18mins
• Building and Enhancing Speech Recognition Models 19mins