Developing Automatic Speech Recognition System (ASR) included the knowledge of several areas such as linguistics, computer science, mathematics, and electrical engineering. The Speech Recognition Systems course is designed to introduce you to the modern concepts of ASR along.
When a person speaks, he produces a time-varying pattern of sounds or waves that are transmitted through the air and captured by a sensor like a microphone and turned into a sequence of numbers representing the pressure change over time. ASR converts the time-pressure signal into a time-frequency-energy signal. The course teaches you how to do all these for creating an ASR system.
After completing the course, you will be able to build a speech recognition system almost entirely using Python.
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
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Course Credit: Microsoft
|Before Your Start||00:03:00|
|Background and Fundamental Theory|
|Module 1: Introduction||00:02:00|
|Module 1: Lab Introduction||00:01:00|
|Speech Signal Processing|
|Module 2: Introduction||00:02:00|
|Module 2: Lab Introduction||00:01:00|
|Module 3: Introduction||00:03:00|
|Module 3: Lab Introduction||00:02:00|
|Module 4: Introduction||00:04:00|
|Module 4: Lab Introduction||00:03:00|
|Module 5: Introduction||00:03:00|
|Module 5: Lab Introduction||00:04:00|
|Advanced Acoustic Modeling Techniques|
|Module 6: Introduction||00:04:00|
|Submit Your Assignment||00:00:00|
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