Audio Content Analysis. Juan Pablo Bello EL9173 Selected Topics in Signal Processing: Audio Content Analysis NYU Poly
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1 Audio Content Analysis Juan Pablo Bello EL9173 Selected Topics in Signal Processing: Audio Content Analysis NYU Poly
2 Juan Pablo Bello Office: Room 626, 6th floor, 35 W 4th Street (ext ) Office Hours: Tuesdays 2-5pm jpbello@nyu.edu Personal webpage: This course:
3 Audio Content Analysis Research, development and application of systems and techniques intended for the automatic analysis and understanding of sounds, in other words, the development of listening machines. Grounded in the combined use of theories, concepts and methods from signal processing, computer science, acoustics (psycho-, bio-, -ecology), cognition, speech science, and music. Sounds: speech, music, environmental sound Audio Signal Processing? Computational Auditory Scene Analysis? Computer Audition? Machine Listening?
4 For example... Histogram Periodogram Novelty Function Spectrogram nature, bird, woodpecker Orca whale, mating call voice, male, stressed speech, female, newscast music, breakbeat, fast Brit-pop, drum Audio Signal
5 Applications (a few examples)
6 Applications (a few examples)
7 Applications (a few examples)
8 Resources IEEE: publications/periodicals/ ISCA: AES: conferences/, ASA: EURASIP: ISMIR: Others:
9 Calendar: Lectures Week 1-2 Fundamentals, and time-frequency representations Week 3-4 Novelty: onset detection Week 5-6 Periodicity: pitch detection and beat tracking Week 7-8 Timbre: low-level features and spectral envelope Week 9-10 Pitch distribution: chroma, chord and key recognition Week Sound classification
10 Assessment Assignments: 40% (4 x 10% each): announced in class/website, due a week after posting, penalties will apply to delays of up to 20 hours. Mid-term exam: 30% (best 3 out of 4 questions), on Projects: 30% (groups of 2) Proposal (04.12): 5% Final project + presentation (05.10): 25% Class Participation: extra points (attendance, questions, discussions, interest)
11 Calendar: Important dates Spring Spring break Project proposals Mid-term exam Final project submission and presentation
12 Tutoring/Resources TA: TBD USE THE OFFICE HOURS (Tuesdays 2-5pm) All relevant information is (or will be published) on the class website - Please read it carefully and keep checking for updates.
13 Recommended Reading Wang, D. and Brown, G. "Computational Auditory Scene Analysis". John Wiley & Sons (2006) Müller, M. Fundamentals of Music Processing: Audio, Analysis, Algorithms and Applications. Springer (2015) Lerch, A. An Introduction to Audio Content Analysis. John Wiley & Sons (2012) Gold, B., Morgan, N., and Ellis, D. Speech and Audio Signal Processing. 2nd edition, Wiley (2011) Klapuri, A. and Davy, M. (Eds.) Signal Processing Methods for Music Transcription. Springer (2006) Smith, J.O. Mathematics of the Discrete Fourier Transform (DFT). 2nd Edition, W3K Publishing (2007) Witten, I. and Frank, E. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann (2005) Further reading will be recommended as the course progresses.
14 To do INSTALL MATLAB ASAP! Matlab documentation, tutorials, examples: helpdesk/help/techdoc/matlab.html Signal Processing Toolbox documentation, tutorials, examples: Matlab file exchange: loadcategory.do START LOOKING FOR PROJECT TOPIC: Visit resource links, talk to current members of the MARL-MIR group (meets Tuesdays 10am, 6th floor conference room, 35 W 4th Street), Attend relevant seminars (most 1pm).
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