Pitch-detection is a computational technique that estimates the fundamental frequency (F0) of a periodic or quasi-periodic signal, most commonly audio or speech. Parameters: (1) input signal — the waveform or its spectral representation (STFT, cepstrum, or raw); (2) algorithm class — autocorrelation, cepstral, FFT-based, hybrid, or learning-based methods; (3) detectable range — the frequency band the method covers (e.g., 50–5000 Hz for human voice and music); (4) output resolution — the precision of the frequency estimate in Hertz or cents. Persistence: implemented as software libraries and hardware modules in music synthesis, speech recognition, audio analysis, and music information retrieval systems; taught as a core concept in DSP and audio engineering curricula; sustained by active research in computational musicology and speech processing. [formal: pitch-detectio | substrate: mind | horizon: generations | explicit: yes | epoch: 0.05]
Accepted ontology entry
pitch-detection
Pitch-detection is a computational technique that estimates the fundamental frequency (F0) of a periodic or quasi-periodic signal, most commonly audio or speech. Parameters: (1) input signal — the waveform or its spectral representation (S…
Definition
Why it is in scope
Pitch-detection is a human-made computational technique that estimates the fundamental frequency (pitch) of an audio or speech signal. It persists through decades of DSP research, is implemented in music software and speech analysis tools, and is taught as a core concept in signal processing curricula.
Names and aliases
- pitch-detectionen · CANONICAL
Relations from this entry
- cmsps9i0v06eejlssqrjcqyviDERIVED_FROM →
Pitch-detection algorithms and concepts derived from signal processing research — cepstral, autocorrelation, and spectral methods all originate in DSP. Signal processing provided the mathematical framework. Historical direction per Law 7.
- cmsorsyn802qbjlss3cb2ruiyDEPENDS_ON →
Pitch detection needs frequency to operate: it finds the fundamental frequency of a signal. Remove the concept of frequency and pitch detection loses its entire data domain. Removal test passes.
- cmsps9i0v06eejlssqrjcqyviDEPENDS_ON →
Pitch-detection algorithms need signal processing to operate — FFT for spectral analysis, filtering, windowing. Remove signal processing and pitch-detection algorithms collapse. This is not meta-level; it is a genuine operational dependency passing the removal test.
- cmsps9i0v06eejlssqrjcqyviINSTANCE_OF →
Pitch detection IS a signal processing technique (finding periodicity in signals). Per Law 9: specific→general INSTANCE_OF. A competent speaker calls pitch detection 'a type of signal processing.' It IS itself signal processing.
Relations to this entry
- cmsqals7w0004ox1y79lqk3dy← SERVES
Per Law 8d SERVES: cepstral-envelope is extracted specifically to capture the slowly-varying spectral structure, which directly encodes pitch information. Its designed purpose includes enabling pitch estimation from the quefrency-domain representation. Servant (cepstral-envelope)→master (pitch-detection).
- cmst3572m00qn13a440mzzz0b← DEPENDS_ON
Pitch-synchronous overlap-add requires an estimate of the signal's pitch period to align analysis frames synchronously. Remove pitch detection and the method cannot determine period boundaries, so it stops operating as pitch-synchronous.
- pitch-synchronous← DEPENDS_ON
Pitch-synchronous processing requires pitch period information to align analysis windows with pitch cycles. Remove pitch-detection and pitch-synchronous processing stops operating — it cannot function without pitch periods. Constitutive dependency.
Record identity
- Created
- Aug 12, 2026, 7:25 PM UTC
- Content hash
- 42c56e97b7f303ca089bbb56e1ef5c0a66cb1ea80d53340434aad27177284235