This course is part of the Advanced and Applied AI on Microsoft Azure ExpertTrack
Applied Artificial Intelligence: Speech Recognition Systems
Gain an understanding of Automatic Speech Recognition (ASR) systems using Python and AI-powered technology.
Duration
3 weeksWeekly study
5 hoursIncluded in an ExpertTrack
Course 2 of 4
Applied Artificial Intelligence: Speech Recognition Systems
Explore AI-powered technology
This course is part of the Advanced and Applied AI on Microsoft Azure ExpertTrack, helping you develop AI and machine learning skills and prepare you for the relevant Microsoft microcredentials.
This course will teach you the fundamentals of the components of a modern Automatic Speech Recognition (ASR) system. You’ll then put this knowledge into practice by building your own speech recognition system almost entirely out of Python code, a powerful tool used across AI and data science practices.
Delve into Automatic Speech Recognition
When a human speaks a word, they cause their voice to make time-varying patterns of sounds, and waves of pressure that spread through the air.
During this course, you’ll understand how these sounds are captured by a sensor, turned into a sequence of numbers and how an automatic speech recognition system converts this into a textural representation of what was said.
You’ll delve into the components of ASR as well as the fundamental theory and background of speech recognition.
Build your own speech recognition system
You’ll identify the different models and problems when designing Speech Recognition Systems as you build your own. This hands-on approach will help you identify the different components of speech decoding and demonstrate your knowledge and understanding of techniques such as Advanced Acoustic Modelling.
During each lab, you’ll build a different functioning block of the system and by the end of the course, you will have built a speech recognition system almost entirely out of Python code, a powerful tool that you can use across your data science practices.
What topics will you cover?
- Understand the fundamental theory of Speech Recognition
- Be able to demonstrate an understanding of the background of Speech Recognition
- Identify the different models and problems when designing Speech Recognition Systems
- Demonstrate knowledge of Deep Neural Network Acoustic Models
- Understand the vocabulary in Language Modelling
- Identify the different components of Speech Decoding
- Demonstrate an understanding of the techniques of Advanced Acoustic Modelling
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Learning on this course
On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.
What will you achieve?
By the end of the course, you‘ll be able to...
- Fundamentals of Speech Recognition
- Basic Signal Processing for Speech Recognition
- Acoustic Modelling and Labeling
- Common Algorithms for Language Modelling
- Decoding Acoustic Features into Speech
Who is the course for?
This course is aimed at anyone with an understanding of data analysis who has created models using machine learning. Individuals who will benefit from this course include:
- Data Analysts
- Machine Learning Engineers
- Deep Learning Engineers
- Many more professionals involved in the development of AI-based technologies.
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Map your progress
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