1. DEVON BRYANT CS 525 SEMESTER PROJECT Audio Signal MIDI Transcription

2. Music Transcription Extraction of “onset”, “duration”, and “pitch” information from digital audio signals Two-phased approach  Extract Temporal Information (Onset & Duration)  Extract Frequency Information (Pitch) Many applications  MIDI representation for low bandwidth  Sheet music score generation  Comparison against DB for copyright or search

3. Extraction of Temporal Events

4. Spectral Flux – change in magnitude spectrum between consecutive frames “Onsets” = window start, “Offsets” = window stop Audio File Frames FFT Mag

5. Extraction of Pitch Information

6. Process event frames through Fast Fourier Transform (FFT) to bin frequencies Use a-priori instrument knowledge to find fundamental f 0 frequencies in spectrum Event Window Frames FFT f 0 Estimation MIDI File

7. Issues Encountered Noise artifacts or fluctuations can trigger false onsets Frequency resolution on shorter events/notes is poor

8. Results Single Note Scale  Original audio  Transcribed MIDI Chords  Original audio  Transcribed MIDI Short Song  Original audio  Transcribed MIDI

9. Questions?