Disclosure: when you buy through links on our site, we may earn an affiliate commission.

Speaker Recognition | By Award Winning Textbook Author

Audio processing, feature extraction, speaker recognition, machine learning, and neural networks with coding examples
4.5
4.5/5
(41 reviews)
182 students
Created by

9.8

CourseMarks Score®

10.0

Freshness

9.4

Feedback

9.3

Content

Platform: Udemy
Video: 7h 15m
Language: English
Next start: On Demand

Top Machine Learning courses:

Detailed Analysis

CourseMarks Score®

9.8 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

10.0 / 10
This course was last updated on 5/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

9.4 / 10
We analyzed factors such as the rating (4.5/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.3 / 10
Video Score: 8.7 / 10
The course includes 7h 15m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
Detail Score: 9.2 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
33 resources.
10 exercises.
0 test.

Table of contents

Description

This course is an introduction to speaker recognition techniques.

Speaker recognition lies in the intersection of audio processing, biometrics, and machine learning, and has various applications. You can find the application of speaker recognition on your smart phones, smart home devices, and various commercial services.

In this course, we will start with an introduction to the history of speaker recognition techniques, to see how it evolved from simple human efforts to modern deep learning based intelligent systems.

We will cover the basics of acoustics, perception, audio processing, signal processing, and feature extraction, so you don’t need a background in these domains. We will also have an introduction of popular machine learning approaches, such as Gaussian mixture models, support vector machines, factor analysis, and neural networks.

We will focus on how to build speaker recognition systems based on acoustic features and machine learning models, with an emphasis on modern speaker recognition with deep learning, such as the different options for inference logic, loss function, and neural network topologies.

We will also talk about data processing techniques such as data cleansing, data augmentation, and data fusion.

We included lots of hands-on practices and coding examples for you to really master the topics introduced in this course, and a final project to guide you through building your own speaker recognition system from scratch.

If you are a college student interested in AI or signal processing, or a software engineer, system architect or product manager working with related technologies, then this course is definitely for you!

You will learn

✓ Basic concepts and core algorithms in speaker recognition
✓ Audio processing and acoustics
✓ Machine learning and deep learning basics
✓ Coding practice and toolkits for audio and speech
✓ Python and PyTorch for machine learning
✓ Building a speaker recognition system from scratch

Requirements

• College level mathematics
• Experience with machine learning or coding will be a plus

This course is for

• College students or graduate students
• Engineers, researchers, and program managers in universities or industry
• General audience interested in AI
• Fans of cool technology

How much does the Speaker Recognition | By Award Winning Textbook Author course cost? Is it worth it?

The course costs $14.99. And currently there is a 82% discount on the original price of the course, which was $84.99. So you save $70 if you enroll the course now.

Does the Speaker Recognition | By Award Winning Textbook Author course have a money back guarantee or refund policy?

YES, Speaker Recognition | By Award Winning Textbook Author has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Speaker Recognition | By Award Winning Textbook Author course, but there is a $70 discount from the original price ($84.99). So the current price is just $14.99.

Who is the instructor? Is Quan Wang a SCAM or a TRUSTED instructor?

Quan Wang has created 1 courses that got 41 reviews which are generally positive. Quan Wang has taught 182 students and received a 4.5 average review out of 41 reviews. Depending on the information available, Quan Wang is a TRUSTED instructor.
Speech Expert at Google
Dr. Quan Wang is currently a Staff Software Engineer at Google, managing the Speaker, Voice & Language team, and an IEEE Senior Member. He was a former Machine Learning Scientist at Amazon Alexa team. Quan had been leading the efforts to deploy advanced speaker recognition technologies to various products at Google, making Google Home the first smart home speaker to support multiple users in the market.

Quan has authored 50+ impactful patents and papers in speaker recognition, speaker diarization, voice separation, speech detection, language recognition and speech synthesis, with 2500+ citations. Quan’s work has received coverage by top tech media including VentureBeat, TechCrunch, Engage and CNET.

Quan is the author of the textbook “Voice Identity Techniques: From core algorithms to engineering practice”, which was selected by the bestselling books about AI leaderboard in China, and won the Distinguished Author of Year 2020 Award.

9.8

CourseMarks Score®

10.0

Freshness

9.4

Feedback

9.3

Content

Platform: Udemy
Video: 7h 15m
Language: English
Next start: On Demand

Students are also interested in

Review widget (for course creators):

Speaker Recognition | By Award Winning Textbook Author rating
Code for the widget (just copy and paste it to your site):
<a href="https://coursemarks.com/course/speaker-recognition-by-award-winning-textbook-author/" target="_blank" title="Speaker Recognition | By Award Winning Textbook Author on Coursemarks.com"><img border="0" src="https://coursemarks.com/widget/98.svg" width="200px" alt="Speaker Recognition | By Award Winning Textbook Author rating"/></a>