Matlab Evaluate Acoustic Metrics

Evaluate Acoustic Metrics

Select the correct Audio Toolbox function for acoustic measurement, apply proper calibration, and choose appropriate standards — instead of reimplementing algorithms or calling nonexistent functions.

When to Use

• Computing psychoacoustic metrics (loudness, sharpness, roughness, fluctuation)

• Evaluating speech quality or intelligibility (ViSQOL, STOI, STI, SII)

• Assessing noise compliance (NC rating, RC rating, RNC, SIL)

• Measuring SPL from recordings (offline, calibrated)

• Computing broadcast loudness (EBU R 128 / LUFS)

• Measuring reverberation time (RT60) from impulse responses

• Detecting tonal content (tone-to-noise ratio, prominence ratio)

• Converting microphone sensitivity to CalibrationFactor

• User mentions PESQ or POLQA (redirect to correct alternatives)

When NOT to Use

• Real-time streaming audio processing loops — use matlab-process-streaming-audio

• Audio device I/O, recording, or live calibrateMicrophone — use matlab-play-record-audio

• Audio plugin authoring (VST/AU) — use matlab-write-audio-plugin

• General filter design unrelated to measurement — use matlab-design-digital-filter

• Spatial audio / HRTF / SOFA processing

Workflow

Follow this decision tree to route the user's goal to the right function:

1. Identify the measurement goal

2. Ask before computing

Before writing code, confirm these with the user:

• Calibration: Do they have a CalibrationFactor? Did they calibrate with calibrateMicrophone? (See Calibration section)

• Standard: Which standard or method applies? (ISO 532-1 vs 532-2, NC vs RC vs RNC)

• Sound field: Free field or diffuse field recording?

• Application context: What space type? What's the concern? (Drives NC vs RC vs RNC selection)

3. Select function and apply

Use the Key Functions table and the category-specific patterns below.

Functions That Do NOT Exist

Never suggest pesq or polqa. They are not in Audio Toolbox and cannot be added due to licensing.

Key Functions

See references/function-arguments.md for complete argument lists, defaults, and valid values for each function — consult when constructing calls with non-default parameters.

Calibration

CalibrationFactor from microphone sensitivity

Convert dB sensitivity (dBV/Pa) to the linear CalibrationFactor:

sensitivity_dBV = -26;  % Example: -26 dBV/Pa microphone
calibrationFactor = 1 / 10^(sensitivity_dBV/20);

The CalibrationFactor is the 3rd positional argument for acousticLoudness, acousticSharpness, acousticRoughness, and acousticFluctuation (default: sqrt(8)). For noise compliance functions, pass it as a name-value: CalibrationFactor=value.

System-level calibration advice

Always ask the user about their signal chain. If the recording path includes a preamp, audio interface, or ADC with unknown gain, the mic sensitivity spec alone is insufficient. Recommend:

1. Play a 1 kHz tone through the system and record it through the full signal chain (mic → preamp → ADC → WAV). Use a pistonphone for a known 94 dB reference, or place a physical SPL meter next to the microphone to get an SPL reading.

2. Compute the system calibration factor: calibrationFactor = calibrateMicrophone(calRecording, fs, SPLreading, FrequencyWeighting="Z-weighting")

3. Pass that factor to the measurement function

calibrateMicrophone expects a 1 kHz tone recording as input. The SPLreading argument is the known SPL in dB (e.g., 94 from a pistonphone, or the value shown on a physical SPL meter).

Cross-reference: for the physical recording workflow with calibrateMicrophone, see the matlab-play-record-audio skill.

Patterns

Psychoacoustic Metrics

[audioIn, fs] = audioread("recording.wav");
calFactor = 1 / 10^(-26/20);

loudness = acousticLoudness(audioIn, fs, calFactor, ...
    Method="ISO 532-1", SoundField="diffuse", TimeVarying=true);

sharpness = acousticSharpness(audioIn, fs, calFactor, ...
    SoundField="diffuse", TimeVarying=true);

roughness = acousticRoughness(audioIn, fs, calFactor, SoundField="diffuse");

fluctuation = acousticFluctuation(audioIn, fs, calFactor, SoundField="diffuse");

Return types: acousticLoudness returns a scalar (sones) for stationary analysis. With TimeVarying=true, it returns a column vector (time-varying loudness in sones). The second output (specificLoudness) is a matrix (time x critical bands). It does NOT return a struct or timetable.

Ask the user:

• ISO 532-1 (Zwicker, stationary/time-varying) or ISO 532-2 (Moore-Glasberg)?

• Free-field or diffuse-field recording?

• Time-varying analysis needed?

See references/psychoacoustic-metrics.md for method selection guidance (ISO 532-1 vs 532-2), interpretation tables (sone values, sharpness/roughness/fluctuation scales), tonality metric selection, and combined sound quality assessment workflows.

Unit Conversions

Use built-in functions — do NOT reimplement conversion formulas manually:

When the user specifies a standard (e.g., "ISO 532-2"), pass it as the second positional argument for phon2sone/sone2phon. For hz2mel/mel2hz, use the MelStyle name-value pair.

Noise Compliance

Choose the function based on the application:

[audioIn, fs] = audioread("office_noise.wav");

[NC, SIL, specImbalance, rattleRisk] = noiseCriteria(audioIn, fs, ...
    CalibrationFactor=2.3);

[RC, LMF, QAI, rattleRisk] = roomCriteria(audioIn, fs, ...
    CalibrationFactor=2.3);

SIL = speechInterferenceLevel(audioIn, fs, CalibrationFactor=2.3);

rec = noiseCriteriaRecommendations("NC", Occupancy="all");

Return types:

• NC is a string (e.g., "NC-35" or "NC-56 (1000 Hz)" if a band exceeds)

• RC is a string (e.g., "RC-32(N)" — the letter indicates spectrum quality: N/R/H/RV)

• SIL and LMF are double scalars (dB)

• QAI is a double scalar (dB; 0 = ideal neutral)

• specImbalance and rattleRisk are structs with .Summary (string) and .Details (table) — access .Summary for display. Exception: specImbalance degrades to a char scalar (not a struct) when NC exceeds the curve range (e.g., "Above NC-70") or falls below NC-15. Guard with isstruct(specImbalance) before dot-indexing.

• noiseCriteriaRecommendations requires a criteria name argument: "NC", "RNC", or "RC"

Ask the user:

• What type of space? (office, classroom, hospital, concert hall)

• Is the noise source HVAC? → prefer roomCriteria

• Is the noise steady or fluctuating? → if fluctuating, use roomNoiseCriteria

See references/noise-compliance.md for detailed output interpretation and selection guidance.

Speech Quality

[degraded, fs] = audioread("processed_speech.wav");
[reference, ~] = audioread("reference_speech.wav");

mosScore = visqol(degraded, reference, fs, Mode="speech");

intelligibility = stoi(degraded, reference, fs);

Critical: stoi and visqol argument order is (processed, reference, fs) — processed/degraded signal FIRST.

visqol modes: "speech" for narrowband/wideband speech (outputs 1-5 MOS), "audio" (default) for general audio.

STI/SII Measurement

Two methods are available for both speechTransmissionIndex and speechIntelligibilityIndex:

IR-based method (simpler — no alignment needed):

[ir, fs] = audioread("room_impulse_response.wav");
sti = speechTransmissionIndex(ir, fs);
sii = speechIntelligibilityIndex(ir, fs);

Direct method (from test signals transmitted through the system):

fs = 48000;
reference = stipaExcitation(fs, Duration=15);
% Transmit reference through system, record as 'processed'
[processed, ~] = audioread("received_stipa.wav");

% IMPORTANT: Align signals before computing (see Signal Alignment)
processed = alignsignals(processed, reference);

sti = speechTransmissionIndex(processed, reference, fs);

Ask the user:

• Do they have an impulse response? → use IR method (simpler, no alignment needed)

• Measuring live? → generate test signal, transmit, record, align, compute

• STI or SII? STI for room/PA systems (IEC 60268-16); SII for hearing/communication (ANSI S3.5)

See references/sti-measurement.md for STI NV arguments, post-processing adjustment workflow (Annex M), test signal generation, and result interpretation. See references/sii-measurement.md for SII standard clause selection (5.1-5.3), BandImportanceFunction guidance, measurement positioning, and result interpretation.

SPL Measurement (Offline)

[audioIn, fs] = audioread("recording.wav");

spl = splMeter(SampleRate=fs, ...
    Bandwidth="Full band", ...
    FrequencyWeighting="A-weighting", ...
    TimeWeighting="fast", ...
    CalibrationFactor=2.3);

[Lt, Leq, Lpeak, Lmax] = spl(audioIn);

% For a single overall value, read the final row
fprintf("Leq: %.1f dB(A)\n", Leq(end));

Valid Bandwidth values: "Full band" (overall level), "1 octave", "2/3 octave", "1/3 octave". There is no "broadband" option — use "Full band" for a single overall SPL value.

Output arity: All outputs (Lt, Leq, Lpeak, Lmax) have one row per input sample. For a 12-second file at 44.1 kHz, that is 539,648 rows. Never fprintf or disp the full output — it will hang. Instead:

• Single overall value: read Leq(end) (the final accumulated value)

• Time-interval readings: downsample to interval boundaries: Leq(round(fs*T):round(fs*T):end, :) where T is the desired interval in seconds

TimeInterval controls the integration window for Leq computation but does NOT reduce the number of output rows.

Do not manually compute 20*log10(rms(audioIn)/20e-6) — splMeter handles calibration, weighting, and time integration correctly per IEC 61672.

Multi-band (octave-band) SPL: Use splMeter with Bandwidth="1 octave" — do NOT use octaveFilterBank + manual dB conversion. Key properties for octave-band SPL:

[audioIn, fs] = audioread("recording.wav");

spl = splMeter(SampleRate=fs, ...
    Bandwidth="1 octave", ...
    FrequencyWeighting="Z-weighting", ...
    TimeWeighting="fast", ...
    FrequencyRange=[15 8000], ...
    OctaveFilterOrder=8, ...
    CalibrationFactor=2.3);

[Lt, Leq, Lpeak, Lmax] = spl(audioIn);
cf = getCenterFrequencies(spl);

Critical gotchas for octave-band splMeter:

• Property name is OctaveFilterOrder (not FilterOrder). FilterOrder does not exist on splMeter.

• FrequencyRange compares against true center frequencies (fc = 1000 × 10^(3b/10) per IEC 61260), not nominal values. A band is included only if its true center falls within [lower, upper]. Bands below 1 kHz have true centers slightly above nominal (e.g., "63 Hz" = 63.10); bands above 1 kHz have true centers below nominal (e.g., "2 kHz" = 1995.26, "8 kHz" = 7943.28). Use floor(true_center) for lower bounds and ceil(true_center) for upper bounds. Common case "16 Hz to 8 kHz": use [15 8000] — the 16 Hz true center is 15.85 (so 15 ≤ 15.85 includes it) and 8 kHz true center is 7943 (so 8000 ≥ 7943 includes it). Do NOT use [16 8000] — this drops the 16 Hz band.

• Output is per-sample (see Output arity note above). Never print the full output. For time-interval readings, downsample: Lt100ms = Lt(round(fs*0.1):round(fs*0.1):end, :);

See references/spl-measurement.md for weighting selection guidance (A/C/Z and fast/slow), SPL interpretation tables, occupational exposure limits, splMeter vs poctave equivalency, and common measurement scenarios.

Broadcast Loudness (EBU R 128)

[audioIn, fs] = audioread("broadcast_content.wav");
[loudness, loudnessRange] = integratedLoudness(audioIn, fs);

% Check compliance: target is -23 LUFS +/- 1 LU
isCompliant = abs(loudness - (-23)) <= 1;

Use integratedLoudness for offline compliance checks. Use loudnessMeter for streaming/real-time monitoring (see matlab-process-streaming-audio).

RT60

[ir, fs] = audioread("room_ir.wav");
rtsummary = rt60(ir, fs, Bandwidth="1 octave");

Ask the user:

• What is the room type? (drives the target RT60)

• Do they have an IR, or do they need to measure one?

• T30 (standard) vs T20 (when noise floor limits dynamic range)?

See references/rt60-measurement.md for target RT60 values by space type, T20/T30/EDT interpretation, frequency-dependent analysis, and relationship to STI.

Tonality

[audioIn, fs] = audioread("machine_noise.wav");

[tnr, tnrFreq, isProminent] = acousticToneToNoiseRatio(audioIn, fs);

[pr, prFreq, isProminent] = acousticProminenceRatio(audioIn, fs);

All outputs are empty (0×1) when no tonal components are detected. Check isempty(tnr) before indexing.

Standards-Compliant Filters (Custom Preprocessing)

The metric functions above perform standards-compliant filtering internally. Use standalone filter objects only for custom measurement workflows where no single metric function applies AND you do not need SPL output:

% A-weighting filter
wf = weightingFilter("A-weighting", fs);
weightedSignal = wf(audioIn);

% Octave-band filter bank (for waveform-level band decomposition only)
ofb = octaveFilterBank("1 octave", fs, ...
    FrequencyRange=[31.5 16000], FilterOrder=8);
bandSignals = ofb(audioIn);

If you need octave-band SPL levels, use splMeter with Bandwidth="1 octave" instead of octaveFilterBank + manual dB conversion. See the Multi-band SPL section above.

Signal Alignment

For the direct (processed, reference, fs) method, always align signals:

processed = alignsignals(processed, reference);

SII is more sensitive to misalignment than STI. At 50 ms delay: SII error ~0.016, STI negligible. At 200 ms: SII ~0.036, STI ~0.017. The IR-based (ir, fs) method avoids alignment issues entirely.

Common Mistakes

Conventions

• Always ask about the user's measurement goal before selecting a function

• Always ask about calibration — recommend calibrateMicrophone for system-level accuracy

• Default to SoundField="free" for anechoic/outdoor, "diffuse" for reverberant rooms

• Default to Method="ISO 532-1" for loudness (Zwicker method, most common)

• Use IR-based methods for STI/SII when an impulse response is available (avoids alignment)

• Pass CalibrationFactor explicitly rather than pre-scaling the signal

• For noise compliance, prefer roomCriteria for HVAC and noiseCriteria for general background noise

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