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Also see Harmonies" is a presentation I have given in both highschool and college classrooms.
At each step during sampling a value is drawn from the probability distribution computed by the network.
This value is then fed back into the input and a new prediction for the next step is made.
Other perceptual features are related to sound spectra and how they vary with time.
For example, tonal “brightness” is strongly connected to the centroid or tilt of a spectrum.
“Attack impact” (sometimes called “bite” or “attack sharpness”) is strongly connected to spectral features during the first 20–100 ms of sound, as well as the rise time of the sound.
Figure 2: Analysis of piano notes using analyze.m Download sound file of a piano playing: A0 A1 A2 A3 (low A) A4 (middle A) A5 (high A) Figure 3: Analysis of several instruments using analyze.m Download sound file of instruments playing A4 (middle A): tuning fork flute violin singer Sound Library includes clips of numerous musical instruments and sounds.
For synthesizing a wide variety of musical sounds, it is important to understand which acoustic properties of musical instrument sounds are related to specific perceptual features.
Some properties are obvious: Amplitude and fundamental frequency easily control loudness and pitch.
Building up samples one step at a time like this is computationally expensive, but we have found it essential for generating complex, realistic-sounding audio.
Wave Nets open up a lot of possibilities for TTS, music generation and audio modelling in general.