YoVDO

Mel-Frequency Cepstral Coefficients Explained Easily

Offered By: Valerio Velardo - The Sound of AI via YouTube

Tags

Audio Signal Processing Courses Machine Learning Courses Speech Recognition Courses

Course Description

Overview

Explore the intricacies of Mel-Frequency Cepstral Coefficients (MFCCs) in this comprehensive 58-minute video tutorial. Delve into the concept of Cepstrum, its intuition, and the process of extracting MFCCs, which are widely used in speech and music processing. Learn about the historical context of Cepstrum, visualization techniques, and the role of MFCCs in understanding the vocal tract and speech generation. Discover how to compute and visualize MFCCs, understand their applications and limitations, and gain insights into speech formalization and component separation. Access accompanying slides for enhanced learning and join a community of AI enthusiasts for further discussions and networking opportunities.

Syllabus

Intro
Join the community!
An historical note on Cepstrum
Computing the cepstrum
Visualising the cepstrum
The vocal tract
Speech generation
Understanding the cepstrum
Formalising speech
The goal: Separating components
Computing Mel-Frequency Cepstral Coefficients
Why Discrete Cosine Transform?
How many coefficients?
Visualising MFCCS
MFCCs disadvantages
MFCCs applications
What's up next?


Taught by

Valerio Velardo - The Sound of AI

Related Courses

Audio Signal Processing for Music Applications
Stanford University via Coursera
Binaural Hearing for Robots
Inria (French Institute for Research in Computer Science and Automation) via France Université Numerique
Inside the Music & Video Tech Industry
Kadenze
Extracting Information From Music Signals
University of Victoria via Kadenze
Real-Time Audio Signal Processing in Faust
Stanford University via Kadenze