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Pitch

Pitch is the perceptual property of a sound corresponding to its perceived highness or lowness.

How 2 Manning books explain it

Learn Generative AI with PyTorch

The perceived highness or lowness of a musical sound, determined here by the note’s frequency and encoded by pitch numbers.

How it is used
Represents musical note height numerically so music datasets and sequence models can process performance events.
How deep it goes
Explains frequency, octaves, semitones, and 0–127 pitch numbers, then applies them to MIDI events and tokenization.
Examples
Uses C4, F3, A4, A5, D5, and numbered note_on and note_off events.
What you can do after
Apply it via MIDI pitch values and distinguish note height from velocity when representing music for sequence models.

Read how Learn Generative AI with PyTorch explains pitch →

Learn Haskell by Example

Pitch is the perceptual property of a musical sound associated with its perceived highness or lowness and position in the system of musical tones.

How it is used
Controls synthesizer tone generation and models pitches for musical composition.
How deep it goes
Explains type-class conversion, semitone tuning, chromatic notes, heterogeneous storage, and melody rendering.
Examples
Demonstrates concert A, octave doubling, chromatic note constructors, heterogeneous pitch lists, and a rendered melody.
What you can do after
Build pitch representations, convert them to frequencies, combine them in compositions, and render tones to a WAV file.

Read how Learn Haskell by Example explains pitch →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.