Skip to main content
Back to course
Log in
Get started
Someone wanted to learn this too, so Grasp built them a personal learning path.
Create your own
Audio AI Researcher & Developer
ยท
Module 1
Foundations of Digital Audio
1
Modeling Sound Waves: Amplitude, Frequency, and Phase
Model a sound wave mathematically using its properties of amplitude, frequency, and phase.
2
Understanding Sampling and Aliasing
Explain the Nyquist-Shannon sampling theorem, derive its formula, and demonstrate the effect of aliasing.
3
Quantization and Bit Depth: Foundations of Audio Fidelity
Describe the process of quantization and the role of bit depth in determining audio fidelity.
4
Audio Formats & Channels: A Comparison
Compare and contrast common digital audio formats (WAV, FLAC, MP3) and channel layouts (mono, stereo).
5
Audio Manipulation with FFmpeg
Perform audio format conversion, resampling, and channel manipulation using ffmpeg commands.
6
Loading Audio in PyTorch with torchaudio
Load, decode, and represent audio tensors in PyTorch using torchaudio's I/O backends.
7
Audio Waveforms: Visualization and Basic Time-Domain Operations
Visualize and interpret audio waveforms and perform basic time-domain operations like trimming and concatenation.
8
Audio Normalization Techniques and Use Cases
Apply various audio normalization techniques (peak, RMS, LUFS) and explain their use cases.
Previous module
Next module
Spectral Analysis of Audio Signals