Speech Recognition Systems

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Enrollment in this course is by invitation only

About this course

Developing and understanding Automatic Speech Recognition (ASR) systems is an inter-disciplinary activity, taking expertise in linguistics, computer science, mathematics, and electrical engineering.

When a human speaks a word, they cause their voice to make a time-varying pattern of sounds. These sounds are waves of pressure that propagate through the air. The sounds are captured by a sensor, such as a microphone or microphone array, and turned into a sequence of numbers representing the pressure change over time. The automatic speech recognition system converts this time-pressure signal into a time-frequency-energy signal. It has been trained on a curated set of labeled speech sounds, and labels the sounds it is presented with. These acoustic labels are combined with a model of word pronunciation and a model of word sequences, to create a textual representation of what was said.

Instead of exploring one part of this process deeply, this course is designed to give an overview of the components of a modern ASR system. In each lecture, we describe a component's purpose and general structure. In each lab, the student creates a functioning block of the system. At the end of the course, we will have built a speech recognition system almost entirely out of Python code.

Please Note: Learners who successfully complete this course can earn a CloudSwyft digital certificate and skill badge - these are detailed, secure and blockchain authenticated credentials that profile the knowledge and skills you’ve acquired in this course.

What you'll learn

Fundamentals of Speech Recognition
Basic Signal Processing for Speech Recogntion
Acoustic Modeling and Labeling
Common Algorithms for Language Modeling
Decoding Acoustic Features into Speech

Prerequisites

Some python experience
Basic Machine Learning principles
Knowledge of probability and statistics

Meet the instructors

Adrian Leven

Content Developer
Microsoft Corporation

Adrian Leven is a Content Developer at Microsoft Learning with a focus on Human-Computer Interaction. He received his B.S. In Computer Science from Stanford University.