Module #1 Introduction to Acoustic Signal Processing Overview of acoustic signal processing, its applications, and importance
Module #2 Fundamentals of Acoustics Review of basic acoustic concepts:sound waves, frequency, amplitude, and phase
Module #3 Signal Representation Time-domain and frequency-domain representations of signals, including Fourier Transform
Module #4 Types of Acoustic Signals Classification of acoustic signals:speech, music, noise, and bio-acoustic signals
Module #5 Acoustic Signal Acquisition Microphones, transducers, and other devices for capturing acoustic signals
Module #6 Analog-to-Digital Conversion Conversion of analog acoustic signals to digital signals, including sampling and quantization
Module #7 Digital Signal Processing Fundamentals Introduction to digital signal processing:filtering, convolution, and Fourier Transform
Module #8 Filtering in Acoustic Signal Processing Applications of filtering:noise reduction, equalization, and feature extraction
Module #9 Acoustic Feature Extraction Methods for extracting meaningful features from acoustic signals:spectral features, cepstral features, and more
Module #10 Speech Signal Processing Specific techniques for processing speech signals:speech recognition, speaker identification, and speech enhancement
Module #11 Music Signal Processing Specific techniques for processing music signals:music information retrieval, music classification, and audio effects
Module #12 Noise Reduction and Cancellation Techniques for reducing and cancelling noise in acoustic signals:adaptive filtering, spectral subtraction, and more
Module #13 Acoustic Signal Enhancement Methods for improving the quality of acoustic signals:de-noising, de-reverberation, and equalization
Module #14 Beamforming and Array Processing Techniques for processing signals from microphone arrays:beamforming, direction-of-arrival estimation, and source separation
Module #15 Acoustic Event Detection and Classification Techniques for detecting and classifying acoustic events:sound recognition, anomaly detection, and more
Module #16 Applications of Acoustic Signal Processing Real-world applications of acoustic signal processing:hearing aids, speech recognition systems, and more
Module #17 Deep Learning for Acoustic Signal Processing Introduction to deep learning techniques for acoustic signal processing:convolutional neural networks, recurrent neural networks, and more
Module #18 Acoustic Signal Processing in Python Hands-on implementation of acoustic signal processing techniques using Python libraries:NumPy, SciPy, and Librosa
Module #19 Acoustic Signal Processing in MATLAB Hands-on implementation of acoustic signal processing techniques using MATLAB and its toolboxes
Module #20 Challenges and Future Directions Current challenges and future directions in acoustic signal processing:robustness, adaptability, and explainability
Module #21 Case Studies in Acoustic Signal Processing Real-world case studies of acoustic signal processing applications:cochlear implants, voice assistants, and more
Module #22 Project Development and Presentation Guided project development and presentation on an acoustic signal processing topic of student choice
Module #23 Acoustic Signal Processing for Biomedical Applications Specific applications of acoustic signal processing in biomedical engineering:medical imaging, health monitoring, and more
Module #24 Acoustic Signal Processing for Environmental Monitoring Specific applications of acoustic signal processing in environmental monitoring:wildlife monitoring, oceanography, and more
Module #25 Course Wrap-Up & Conclusion Planning next steps in Acoustic Signal Processing career
