Audio is a fundamental modality of data that has immense utility and need in human communication, digital transmission, pattern discovery, ecological understanding, healthcare, and many more. Advancements in sensor technology, signal processing, and machine learning have led to audio as an asset in many vertical applications. Audio Signal Processing: Advanced Analysis and Machine Learning Applications covers the basics of audio signal processing and analysis from sensing, acquisition, digitization, filtering, denoising, modelling, feature analysis, machine learning, and pattern recognition/decision making. It provides practical examples, illustrations, lab exercises, and mini projects to enhance the learning experience. Provides comprehensive coverage of audio signal analysis. Offers problem sets and laboratory exercises that cover a wide range of audio signals, models, and algorithms. Enables foundational knowledge that can translate into other domains of signal processing.