Fig. 2
From: Detecting fingering of overblown flute sound using sparse feature learning
Overall schematic of proposed flute fingering detection system. The system takes an audio waveform as an input, and four consecutive frames of a 128-bin mel-scale spectrogram are concatenated to learn timbral features. Note that features are learned only from training data. Obtained feature activations are max-pooled and standardized prior to training the classifier