Audio Signal Processing Concepts Explained with Python#
This Jupyter Book is a collection of interactive notebooks designed to visually explain fundamental concepts in audio signal processing using Python. Through plots and examples, the book aims to provide an intuitive understanding of digital signal processing (DSP) techniques, making them accessible to a broad audience, including students, sound engineers, and music producers.
The book is organized into four main sections:
Fundamentals of Audio Signal Processing: Establishes the Core DSP principles, such as sampling, quantization, and linear systems, laying the groundwork for more advanced topics.
Time and Frequency Domain Analysis: Covers signal analysis, focusing on both time-domain and frequency-domain techniques, essential for any audio processing task.
Measuring and Analyzing Audio Signals: Focuses on tools and methods for practical audio measurement, such as normalization, loudness, and signal descriptors.
Room Acoustics: Covers spatial audio processing, reverb, and techniques for simulating room effects, ideal for sound engineers working with acoustics.
Note
Please consider that this book is maintained as an open-source project, and contributions are welcome. If you find any errors, typos, or have suggestions for improvement, please feel free to open an issue or submit a pull request on the GitHub repository
Fundamentals of Audio Signal Processing
Time and Frequency Domain Analysis
Measuring and Analyzing Audio Signals
Room Acoustics
Appendix
Additional Information
References