Enroll Course: https://www.coursera.org/learn/audio-signal-processing
Are you fascinated by the intricate workings of music? Do you want to understand how sounds are analyzed, synthesized, and transformed? Then look no further than Coursera’s ‘Audio Signal Processing for Music Applications’ course. This comprehensive program delves deep into the methodologies of audio signal processing specifically tailored for music, offering practical insights applicable in real-world scenarios.
The course begins with a solid foundation, introducing the fundamental mathematics and essential software tools, including Python and the specialized sms-tools package. You’ll quickly move on to mastering the Discrete Fourier Transform (DFT), understanding its equations, and implementing it in Python to analyze sound. The syllabus then explores crucial Fourier theorems like linearity, shift, and convolution, demonstrating their application in analyzing simple periodic signals and complex sounds.
A significant portion of the course is dedicated to the Short-Time Fourier Transform (STFT), where you’ll learn about windowing, FFT size, hop size, and the crucial time-frequency compromise. Practical demonstrations on computing spectrograms and implementing windowing in Python will solidify your understanding.
Further modules introduce powerful models for understanding music: the Sinusoidal Model, the Harmonic Model, and the Sinusoidal plus Residual Model. You’ll learn to detect spectral peaks, analyze and synthesize sounds using these models, and even implement pitch detection algorithms. The course culminates in exploring sound transformations using STFT, sinusoidal, and harmonic plus residual models, enabling you to manipulate audio in creative ways.
Beyond the technical aspects, ‘Audio Signal Processing for Music Applications’ also covers sound and music description, guiding you through extracting audio features, clustering sounds, and utilizing tools like Sonic Visualiser and the Freesound API. The concluding topics offer a glimpse into advanced areas and resources for continued learning.
This course is an excellent choice for aspiring music technologists, sound engineers, researchers, or anyone with a passion for music and technology. Its hands-on approach, coupled with open-source software, makes complex concepts accessible and practical. Highly recommended!
Enroll Course: https://www.coursera.org/learn/audio-signal-processing