signal-processing

Signal processing fundamentally requires mathematical operations to operate — Fourier transforms, convolutions, filtering all depend on mathematical theory. Remove mathematics and signal processing cannot perform any of its core operations. The removal test passes: without mathematics, signal processing ceases to function.

Filter design is a specific technique within the field of signal processing — it designs filters to shape signal spectra. A competent speaker would describe filter design as 'a signal processing technique.' INSTANCE_OF per Law 9.

Spectral analysis is a specific signal processing technique that examines the frequency content of signals. A competent speaker would call it 'a signal processing method.' INSTANCE_OF per Law 9.

Cepstrum-coefficients are computed specifically to serve signal-processing: they are features extracted from signals for pattern recognition within signal-processing pipelines (speech recognition, fault detection). For whose sake? The coefficients point at signal-processing as their master domain.

Magnitude-spectrum is computed specifically to serve signal-processing: it represents signal power distribution across frequency for diagnostic and analytical purposes. For whose sake? The spectrum points at signal-processing as its master domain.

Cepstral-analysis is the analysis technique performed IN THE cepstral domain, specifically for extracting features from signals. For whose sake? Signal-processing — cepstral methods (MFCC, etc.) are designed as diagnostic tools within signal-processing pipelines.

Spectral-analysis extracts frequency-domain information from signals for diagnostic purposes. For whose sake? Signal-processing — spectral analysis is a core technique within signal-processing, not a standalone practice.

MFCC is a feature extraction technique specifically designed for signal-processing applications (speech recognition, audio classification). For whose sake? Signal-processing — the entire pipeline (Mel filterbank, DCT) exists to serve diagnostic analysis of signals. Valid SERVES (Law 8d).

The cepstrum was developed and is maintained for the sake of signal processing — speech analysis, fault detection, and related applications. For whose sake? Signal processing. The cepstrum is a tool designed to serve signal processing tasks.

The mel-scale was created and is maintained for the sake of signal-processing — specifically speech recognition, audio analysis, and music information retrieval. For whose sake? Signal-processing. The scale is a tool designed to serve this domain's need for perceptually-uniform frequency representation. SERVES direction (servant→master) is correct.

The cepstral domain is a mathematical framework deliberately designed and maintained for the purpose of signal processing — specifically for extracting features from signals that are not easily captured in the frequency domain. Per Law 8d: cepstral-domain SERVES signal-processing because its designed purpose is to further signal-processing operations. The servant (cepstral domain) points at the master (signal processing).

Cross-correlation is a specific signal processing technique that measures similarity between two signals as a function of displacement. It is a canonical instance of signal processing operations.

The cepstrum (1963) derived from the needs and methods of signal processing. It was invented by applying signal-processing operations (FFT, log, IFFT) to exploit the periodic structure in spectra. Signal processing as a field predates and enables the cepstrum concept.

STFT was developed within and derives from the field of signal processing. It addresses a specific signal-processing need — analyzing non-stationary signals — by extending Fourier methods to the time-varying domain.

Spectral-feature concepts derive from signal processing — they are the measurable properties of signals' spectra that engineers and researchers extract and use within signal processing workflows.

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.

Noise reduction is a specific kind of signal processing — techniques (filtering, spectral subtraction, wavelet denoising, etc.) applied to reduce unwanted noise while preserving the desired signal.

Noise reduction operates on signals using signal processing techniques (filtering, spectral subtraction, FFT-based methods). Remove signal processing and noise reduction stops operating — present-tense operational dependency (Law 8). The edge-test confirms signal-processing is the older/more-foundational concept.

Signal processing as a field (1940s-1950s) predates linear predictive coding (developed late 1950s-1960s by BesselSEN, Itakura, and Saito for speech compression). Signal processing provided the theoretical framework — autoregressive modeling, least-squares optimization — that LPC builds on. Direction test per Law 7: signal-processing existed first and fed into LPC.

audio-restoration IS a specific kind of signal processing: it applies mathematical techniques to signals (audio) to remove degradation, noise, and artifacts. A competent speaker would call it 'a kind of signal processing.' This is the nearest kind — no more specific signal-processing subcategory exists.

amplitude-analysis IS a specific kind of signal processing: it applies mathematical techniques to extract and quantify amplitude characteristics of signals (envelope detection, peak measurement, RMS). A competent speaker would call it 'a kind of signal processing.' This is the nearest kind — no 'signal-analysis' entry exists, and amplitude analysis is distinct from spectral-analysis (time-domain vs frequency-domain).

Hop-size as a signal processing parameter (interval between successive analysis windows) emerged from the practice of signal processing. Signal processing existed first and fed into the development of hop-size as a concept.

Spectral reconstruction is built and maintained for the sake of signal processing — its designed purpose is to restore complete spectral information so that signal processing downstream can operate on it. For whose sake? The reconstruction serves the broader signal processing practice.

Speech recognition depends on signal processing for feature extraction (STFT, MFCC, filterbanks), noise reduction, and temporal modeling. Remove signal processing and speech recognition has no computational framework. The removal test passes.

A spectrogram is designed and maintained for the sake of signal analysis — it visualizes spectral content over time to extract information from signals. Its purpose is by design: to serve engineers and scientists analyzing signals. SERVES arrow: spectrogram → signal-processing (servant points to master).

Griffin-Lim is an iterative phase-recovery algorithm designed to reconstruct audio signals from magnitude spectra. Its entire purpose is to serve signal processing — specifically audio reconstruction and speech processing. SERVES: servant (algorithm) → master (domain it serves).

Pitch tracking is a specific kind of signal processing technique — a competent speaker would call it 'a signal processing method.' It answers exactly the INSTANCE_OF question: is X a specific case of the general Y?

Autocorrelation is a specific signal processing technique for measuring signal self-similarity at different time lags. A competent speaker would call it 'a signal processing method.' Specific→general per Law 9.

Dynamic-range-compression is a specific kind of signal processing technique that modulates the amplitude envelope of a signal. A competent speaker would call it a signal processing method. Specific→general per Law 9.

Short-time Fourier transform is designed and maintained for the sake of signal-processing: it enables time-frequency analysis which is the core task of the discipline. Its entire purpose is to further signal-processing operations.

Phase vocoder is a signal processing technique designed for the sake of signal-processing: it enables time-scale modification and phase manipulation in audio, core operations within the discipline.

Spectral entropy is a signal processing measure designed for the sake of signal-processing: it quantifies spectral complexity, a core analytical task within the discipline. Its purpose is to further signal-processing analysis.

Onset detection is a signal processing technique designed for the sake of signal-processing: it identifies temporal events in audio signals, a core analytical operation used across both general signal processing and music applications.

MIR as a field depends on signal processing for its core operations. Remove signal processing — Fourier transforms, windowing, spectral analysis — and MIR's algorithms collapse entirely. The removal test passes: MIR cannot operate without the signal processing techniques it employs.

Beat-tracking algorithms need signal processing for their core operations — FFT, autocorrelation, spectral analysis. Remove signal processing and beat-tracking algorithms collapse. The removal test passes: beat-tracking does not operate without signal processing infrastructure.

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.

Chroma extraction operates on signal processing to function — FFT, filtering, and spectral analysis are the computational primitives that make chroma computation possible. Remove signal processing and chroma algorithms collapse entirely.

Zero-crossing-rate computation needs signal processing to operate — raw signal sampling, noise filtering, and waveform analysis are required. Remove signal processing and ZCR cannot be computed.

Spectral peak detection needs signal processing to operate — magnitude spectrum computation via FFT, noise floor estimation, and local maximum detection are signal processing primitives. Remove signal processing and spectral peak analysis collapses.

Mel-filterbank computation needs signal processing — FFT to get the magnitude spectrum, and spectral analysis to apply the mel-spaced triangular filters. Remove signal processing and mel-filterbank cannot operate.

Spectral-slope computation needs signal processing to operate: remove signal processing (FFT, filtering, spectral analysis) and spectral-slope cannot be computed. Removal test passes.

window-function is built for the sake of signal processing: window functions are mathematical functions specifically designed to shape signal segments in spectral analysis, filtering, and other signal processing operations. Their designed purpose is to serve signal processing's need to reduce spectral leakage and control side-lobes. Per Law 8d: for whose sake? The servant (window-function) points at the master (signal-processing). Direction: window-function → signal-processing.

Which came first? Signal processing as a field predates source separation as a specific technique. Source separation emerged from within signal processing practice as the problem of separating mixed signals became prominent. Signal processing fed into the development of source separation.

Audio-feature extraction needs signal processing to operate now — it relies on DSP techniques (FFT, filtering, windowing) to extract quantifiable properties from signals. Remove signal processing and audio-feature extraction stops working. The removal test (Law 8) passes.

Source separation algorithms need signal processing techniques (filtering, spectral analysis) to operate now. Remove DSP and source separation stops working. Law 8 removal test passes.

The discrete cosine transform is a specific kind of signal processing technique used for data compression, spectral analysis, and filtering. A competent speaker would call DCT 'a signal processing technique.'

The discrete cosine transform is designed to further signal processing — it is a core tool in signal compression, spectral analysis, and processing pipelines. Its purpose is to serve signal processing applications.

Time-stretching IS a specific kind of signal processing technique — it manipulates the time-domain representation of a signal while preserving certain properties. A competent speaker would call time-stretching 'a signal processing method.' Files against the nearest established kind (signal-processing, since phase-vocoder INSTANCE_OF signal-processing exists but time-stretching → phase-vocoder is DEPENDS_ON which is not transitive for INSTANCE_OF).

Voice activity detection IS a specific kind of signal processing task — it analyzes audio signals to determine whether speech is present. A competent speaker would call VAD 'a signal processing method.' Files against the nearest established kind (signal-processing, since speech-recognition DEPENDS_ON signal-processing is not transitive for INSTANCE_OF).

Spectral manipulation IS a specific kind of signal processing technique — it operates by transforming signals into frequency domain, modifying spectral components, and reconstructing the signal. A competent speaker would describe spectral manipulation as 'a signal processing method.' Clear specific→general per Law 9.

Noise cancellation is a specific kind of signal processing technique. It processes signals to remove unwanted noise components. The nearest general kind is signal processing — a competent speaker would call noise cancellation a signal processing method.

Pre-emphasis is a signal processing technique used to balance spectral energy before further processing. Per Law 8d: the servant points at the master — pre-emphasis exists for the sake of signal-processing pipelines, particularly in speech and audio applications.

Linear prediction is a core technique in signal processing — speech coding, audio compression, and spectral estimation all rely on it. Per Law 8d: the servant points at the master. Linear prediction exists for the sake of signal-processing applications.

Zero-phase filtering is a signal processing technique for preserving phase while filtering. Per Law 8d: the servant points at the master — zero-phase-filtering exists for the sake of signal-processing where phase distortion must be avoided.

Windowing is a specific signal processing technique (applying a taper function to signal segments). Per Law 9: specific→general INSTANCE_OF is correct. A competent speaker would call windowing 'a type of signal processing operation.' It IS itself signal processing, not dependent on it as a separate concept.

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.

Formant warping IS a signal processing technique — it nonlinearly maps formant frequencies in the spectral domain. Per Law 9: specific→general. A competent speaker calls formant warping 'a type of signal processing operation.'

Overlap-add is a specific signal-processing technique for reconstructing signals from overlapping frames; a competent speaker calls it a type of signal processing operation.

Audio-watermark is a specific signal processing technique for data hiding in audio; a competent speaker calls it a type of signal processing operation.

A filter (signal processing filter) is a specific signal processing operation that modifies the frequency content of a signal. A competent speaker calls filtering a type of signal processing technique. Per Law 9: specific→general INSTANCE_OF, nearest kind is signal-processing.

The discrete Fourier transform is a specific signal processing technique for converting time-domain signals to frequency-domain representation. A competent speaker calls DFT a type of signal processing operation. Per Law 9: specific→general INSTANCE_OF. Nearest kind is signal-processing.

Spectral estimation is a specific signal processing technique for estimating the frequency content of signals from data samples. A competent speaker calls it 'a type of signal processing'. Per Law 9.

Time-frequency analysis is a specific signal processing technique that represents signals in both time and frequency domains simultaneously. A competent speaker calls it 'a type of signal processing'. Per Law 9.

The Fourier transform is a specific signal processing technique for decomposing signals into frequency components. A competent speaker calls it 'a type of signal processing'. Per Law 9.

Perceptual weighting is a specific signal processing technique that applies frequency-dependent weighting to audio signals. A competent speaker calls it a type of signal processing.

Audio watermarking as a technique requires signal processing operations — embedding and extraction involve filtering, modulation, and spectral manipulation. Remove signal processing capability and audio watermarking stops operating.

Perceptual weighting is a signal processing technique that weights frequency components according to psychoacoustic models. It requires signal processing operations (filtering, spectral analysis) to implement. Remove signal processing capability and perceptual weighting cannot function.

Auditory scene analysis is a specific computational framework within signal processing that decomposes mixtures using grouping cues and segregation algorithms. A competent speaker calls it a signal processing approach.

Perceptual coding emerged as a specialized branch of signal processing, building on transform coding, quantization theory, and psychoacoustic models developed within the field. The field of signal processing preceded and produced the specific coding technique. Historical derivation, not operational dependency.

An audio-codec's analysis, transformation, and synthesis stages are signal processing operations; remove signal processing and the codec cannot transform audio.

Audio restoration is a signal processing operation — it uses filtering, spectral analysis, noise reduction, and other signal processing techniques to repair degraded audio. Remove signal processing and audio restoration has no methods to operate. Constitutive dependency.

Equalization is a signal processing operation — it applies filter operations to shape frequency response. Remove signal processing techniques (filtering, spectral analysis) and equalization has no means to operate. Constitutive dependency.

Temporal-centroid is computed from audio signal processing — it requires frame-based energy analysis, windowing, and spectral/ временной analysis of audio frames. Remove signal processing and the metric has no computation pathway. Constitutive dependency.

The accepted definition carves audio engineering as the discipline of designing, capturing, processing, and reproducing sound, with parameters that are signal-processing operations: signal-chain design, mixing balance, dynamics processing. Remove signal processing and the discipline loses its processing, mixing, and dynamics tools — only passive acoustic layout remains, which the definition does not carry as its purpose — it stops operating as defined. Same accepted shape as music-information-retrieval →DEP→ signal-processing (ACCEPTED) and audio-feature →DEP→ signal-processing (ACCEPTED).

Measuring audio latency requires signal processing to capture, buffer, and timestamp audio streams; remove signal processing and latency measurement stops operating.

Audio fingerprinting requires signal processing to extract spectral and temporal features from audio. Remove signal processing and the fingerprint extraction stops operating.

Spectral gating operates on frequency-domain representations of signals, requiring FFT/IFFT operations and amplitude thresholding — all signal processing. Remove signal processing and the gate stops working.

Frequency-weighting applies frequency-dependent gain curves to signals — this requires signal processing operations (FFT, filter design, or analog filtering). Remove signal processing and frequency-weighting has no mechanism to operate. Constitutive dependency confirmed.

An audio-plugin operates by performing audio processing; removing signal processing operations would stop the plugin from producing audio output. The removal test is met at operational level.

Phase vocoder performs time-stretching and pitch-shifting via STFT analysis/resynthesis with windowing and phase propagation. All core operations are signal processing; removing signal processing eliminates the mechanism and the vocoder stops operating.

Dithering applies digital signal processing operations to add noise to an audio signal. Remove signal processing and dithering has no mechanism to operate. The removal test passes.

Transform-coding is a specific family of compression techniques that applies transforms such as DCT/MDCT within signal processing operations. It is a specific instance of signal processing, not merely dependent on it.

Codec IS a specific kind of signal-processing system. It applies encoding-decoding transforms, quantization, and entropy coding — all signal processing operations. Law 9: specific→general. A codec is an instance of signal processing, not merely dependent on it.

a-weighting DEPENDS_ON signal-processing. The A-weighting curve requires signal processing for its measurement and application — it is applied via weighting filters in signal processing systems. Removal test: remove signal processing, and a-weighting loses its operational framework for measuring and applying frequency weightings.

Heterodyning (frequency conversion by mixing two signals to produce sum and difference frequencies) is a specific signal processing technique. Law 9 nearest-kind: a competent speaker classifies it as 'a form of signal processing.'

Amplitude modulation is a specific signal processing technique for varying carrier amplitude. Competent speaker test: amplitude modulation is a kind of signal processing. Specific→general, nearest kind.

Sidechain is a specific kind of signal-processing technique: it processes signals by routing one signal to control the processing of another. A competent engineer would call sidechaining a form of signal processing. The nearest kind is signal-processing — broader categories like 'audio technique' or 'method' would be leaps when signal-processing already exists and captures the technical essence.

Phase coherence is a specific signal-processing property used to quantify consistency of phase relationships in audio signals. It is a kind of signal-processing metric, specific→general. Law 9 satisfied.

fir-filter (finite impulse response filter) operates within signal-processing as a constitutive domain. Remove signal-processing as a concept and fir-filter ceases to operate — it is a technique that requires the framework of signal processing to function.

For whose sake: modulation is built to serve signal-processing. Servant points at master.

A minimum-phase filter is designed to minimize phase distortion in signal processing pipelines. It is built and maintained for the sake of signal processing practice — specifically, for applications where preserving causal phase relationships is essential (audio, communications, control systems).

The Butterworth filter is a signal filter specifically designed for signal processing applications — its purpose is to provide a maximally flat frequency response in the passband for signal processing tasks. Servant (butterworth-filter) points at master (signal-processing).

Demodulation is a technique built for the sake of recovering information from modulated carriers within signal processing practice. Remove demodulation and receivers cannot recover the original signal from its modulation — the processing stops operating.

State-space models represent systems through differential equations and state variables, serving signal processing by enabling optimal filtering (Kalman filter), prediction, and system identification. They serve the field by providing a mathematical framework for modeling and processing dynamic signals.

Speech enhancement is a specific signal-processing discipline for improving speech quality. Specific→general.

An expander IS a specific kind of signal-processing: it dynamically increases the dynamic range of a signal by reducing gain for signals above a threshold. Competent speakers would call it a form of signal processing.

Kalman filter is built or maintained for the sake of signal processing: its primary engineering application is denoising and tracking signals in noisy measurements. For whose sake? Signal processing. Servant (filter) → master (processing domain). Law 8d.

Group delay is a specific signal-processing concept that measures the time delay of the envelope of a signal's spectral components as a function of frequency, defined as τg(ω) = −dφ(ω)/dω where φ is phase response. It is an instance of signal-processing — the discipline of algorithms and methods for analyzing and transforming signals. Sense pinned: group delay as the derivative-of-phase concept, not the colloquial sense of a delayed group acting.

Waveshaping IS a specific kind of signal processing: it modifies a signal by applying a nonlinear transfer function. A competent speaker would call waveshaping 'a form of signal processing.' Nearest kind is signal-processing since no intermediate accepted rung exists on this classification path.

Audio mixing depends on signal-processing — it manipulates audio signals through EQ, dynamics, panning, and effects, all of which are signal processing operations. The removal test: remove signal-processing and audio mixing has no conceptual or technical framework for operating on sound.

Mel-cepstral-distortion quantifies perceptual difference between utterances through mel-cepstral coefficient computation — a signal-processing technique. Remove signal-processing (the mathematical analysis and transformation of audio signals) and mel-cepstral-distortion cannot be computed or used. The metric depends on signal-processing for its core computational mechanism.

windowed-sinc-interpolation is built for the sake of signal reconstruction and resampling tasks within signal processing practice.

Spectral-flatness-measure requires signal-processing techniques (FFT, power spectrum estimation) to operate — removing signal-processing means you cannot compute the power spectrum, and the measure ceases to function. This is an operating dependency, not merely a domain label.

Speech intelligibility is a quality metric computed to evaluate and guide signal processing systems that enhance, compress, or transmit speech. It serves signal processing by providing the target objective that processing algorithms optimize for.

windowed-sinc-interpolation IS a specific kind of signal-processing technique — it reconstructs a continuous signal from samples using a sinc kernel modulated by a window function. The nearest kind is signal-processing: operations on signals. Direction is specific→general.

quadrature IS a specific kind of signal processing concept: the use of orthogonal components (90 degrees apart) in signal representation. A competent speaker would call quadrature 'a signal-processing technique/construct'.

decimation IS a specific kind of signal-processing technique — it reduces the sampling rate of a signal by keeping only every Nth sample. The nearest kind is signal-processing: operations on signals. Direction is specific→general.

Phase response is a specific signal-processing concept describing the frequency-dependent phase shift introduced by a system, expressed as the argument (angle) of the complex frequency response H(jω). It is an instance of signal-processing — the discipline of algorithms and methods for analyzing and transforming signals. Sense pinned: phase response as the angular component of frequency response, not the colloquial sense of reacting to something.

cepstral-coefficients are computed via signal-processing operations (FFT, log, DCT). Removing signal-processing stops the computation pipeline. Present-tense removal test passes.

The sampling theorem (Nyquist-Shannon) establishes the conditions for perfect reconstruction of continuous signals from discrete samples and serves signal processing by providing the foundational principle for all digital signal processing — without it, the conversion from analog to digital would lack theoretical guarantees.

Group delay is a concept that emerged from signal processing theory — it quantifies the time delay of signal envelopes through LTI systems, a notion that arose within the discipline of signal processing. Law 7: signal processing (the broader discipline) existed first and fed into the specific concept of group delay.

All-pass filter is a signal-processing technique that modifies phase without altering magnitude. Remove signal-processing and the all-pass-filter concept stops operating — it requires the domain framework to function.

Impulse response is a concept that emerged from signal processing theory — it characterizes LTI systems by their response to a Dirac delta input, a notion central to SP analysis. Law 7: signal processing (the broader discipline) existed first and fed into the specific concept of impulse response.

audio-processing IS a specific kind of signal-processing: it transforms audio signals using techniques like filtering, mixing, and amplification. Pinned sense: processing of audio-frequency signals (as opposed to RF, data, or other signal domains). Nearest kind per Law 9.

Audio-phase is a concept within signal processing — it describes the relative timing of frequency components in an audio signal. Remove signal-processing and audio-phase stops operating as a meaningful concept.

Gain-staging IS a specific kind of signal-processing practice: it involves adjusting signal levels at each stage of an audio chain to optimize the signal-to-noise ratio. It is a procedural form of signal processing.

spectral-processing IS a specific kind of signal-processing. Signal processing is the general method of analyzing and modifying signals; spectral processing is the particular variant that operates in the frequency domain via Fourier transforms and their variants. A competent speaker would call spectral processing 'a kind of signal processing.'

A limiter is a signal processing component built to prevent signal amplitude from exceeding a threshold. It serves the broader signal processing practice by protecting downstream components and controlling dynamic range.

anti-aliasing IS a specific kind of signal-processing technique — it prevents high-frequency components from folding into lower frequencies during sampling. The nearest kind is signal-processing: operations on signals. Direction is specific→general.

Butterworth filter operates as a digital/analog signal processing filter; removing signal processing capability stops it from operating. The filter's computation (frequency response evaluation, pole placement) requires signal processing operations.

Signal-amplification is a specific kind of signal-processing: it processes signals by increasing their amplitude. Nearest kind: signal-processing is the general class of operations that modify signals. Competent speaker: signal-amplification is a type of signal processing. Law 9 passes. Not DEPENDS_ON — it is a kind, not a requirement.

The FIR filter is a digital filter type specifically designed for signal processing — its purpose is to implement linear-phase filtering in signal processing pipelines. Servant (fir-filter) points at master (signal-processing).

iir-filter (infinite impulse response filter) operates within signal-processing as a constitutive domain. Remove signal-processing and the iir-filter concept ceases to operate — it needs the framework to function.

equalization IS a type of signal processing technique. It modifies the frequency content of a signal — specifically adjusting the amplitude of certain frequency bands. A competent speaker would call it 'a signal processing technique.'

Pitch estimation is a specific signal processing technique for estimating fundamental frequency. A competent speaker would call it a kind of signal processing. Law 9 specific→general.

Phase retrieval is a specific signal processing problem class concerned with reconstructing a signal from magnitude information alone. A competent speaker would call phase retrieval a kind of signal processing technique. Law 9 specific→general.

An audio-buffer is a specific data structure used in digital audio systems to hold samples for processing and playback. It is a concrete instance of signal processing infrastructure, used to manage sample data in real time. A competent speaker would call an audio buffer a kind of signal processing component. Law 9 specific→general.

sample-rate-conversion is a specific kind of signal processing: a named procedure that transforms a discrete-time signal between sampling rates via filtering + resampling. A competent DSP practitioner calls it 'a signal-processing technique' — kind-of (Law 9), nearest kind is signal-processing. Not an output (unlike spectrogram) and not a sub-step; it is a full pipeline stage.

Phase unwrapping is a specific signal-processing technique for recovering continuous phase from wrapped measurements. It is a concrete method within signal processing.

FFT is a specific signal processing algorithm for computing the discrete Fourier transform efficiently. A competent DSP practitioner would classify FFT as a signal processing operation. Specific to general per Law 9.

Spectral centroid is a specific signal processing technique that computes the weighted mean of frequencies present in a signal spectrum, producing a single number summarizing spectral shape. A competent DSP practitioner would classify spectral centroid as a signal processing method. Specific to general, Law 9.

A windowing-function (Hann, Hamming, Blackman, etc.) is a specific kind of signal processing tool — a mathematical function applied to a signal to shape its spectral characteristics. It IS a type of signal processing technique/element. Law 9: specific→general.

compression is a signal-processing technique. Remove signal processing and compression has no framework to operate within — its algorithms, theory, and practice all live inside signal processing. Without signal processing, compression cannot function.

Analysis-by-synthesis is a specific class of methods within the broader discipline of signal processing; a competent speaker would call it a signal processing technique.

Pitch-shifting is a specific audio signal processing technique; a competent speaker would call it a signal processing method. Specific→general per Law 9.

spectral-flattening is a specific technique within the broader discipline of signal processing; a competent speaker would call it a signal processing method.

pitch-synchronous-analysis is a specific analysis method within signal processing; a competent speaker would call it a signal processing technique.

Cepstral-domain IS the general class of signal processing that operates in the cepstrum (quefrency) domain. Cepstral-subtraction and cepstral-envelope are both specific techniques within this domain. The nearest common kind for cepstral-domain itself is signal-processing. Law 9: specific→general, nearest kind.

A sample-rate converter is a specific kind of signal processing operation that changes sampling frequency via resampling. Specific→general per Law 9, nearest kind signal-processing.

acoustic-measurement requires signal-processing techniques (FFT, spectral analysis, filtering) to operate. Remove signal-processing and acoustic-measurement has no methodology to extract measurements from signals. Removal test passes.

Audio-watermarking is a specific technique for embedding imperceptible data in audio, a particular method within the broader discipline of signal processing. Specific→general, nearest kind.

Audio-compression needs signal processing to operate now. Remove signal processing — the algorithms for transform coding, quantization, and entropy encoding — and audio compression has no mechanism to reduce data size. Present-tense dependency per Law 8.

Audio watermarking fundamentally requires signal processing to embed and detect imperceptible data in audio waveforms. The embedding operates in the frequency or phase domain using DSP techniques (spread spectrum, DCT/DWT transforms, echo delay modulation). Remove signal processing and watermarking has no mechanism for embedding or detection. Present-tense dependency per Law 8.

Pitch-synchronous analysis aligns analysis windows to the pitch period of a quasi-periodic signal. It operates on spectral representations (FFT magnitude/phase) and requires signal processing for pitch detection and spectral estimation. Remove signal processing and the technique has no framework for its core operations. Present-tense dependency per Law 8.

Analysis-by-synthesis iteratively reconstructs a signal by fitting a parametric synthesis model, requiring signal processing for both the forward analysis (spectral estimation) and inverse synthesis (waveform reconstruction). Remove signal processing and the iterative model-fitting loop has no mechanism. Present-tense dependency per Law 8.