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Features and descriptors

Streaming feature extraction

Files are read in 60-second blocks; nothing is ever held whole in memory. Per take, cached as .npz:

Rate Features
125 ms fast RMS level on W, unweighted and A-weighted (IEC 61672 bilinear IIR)
1 s octave-band powers (31.5 Hz–16 kHz), spectral centroid and flatness (50 Hz–16 kHz), 96-band log-frequency spectrogram row, per-octave pseudo-intensity vectors, broadband DOA (azimuth/elevation, 80–3000 Hz), diffuseness ψ
1 min full-resolution (5.9 Hz bins) mean power spectrum — for narrowband hum tracking, comb/fingerprint analysis, room modes

Spectra come from Welch-style averaged 8192-point Hann FFTs at 0.1 s hops.

Spatial estimators

The pseudo-intensity vector is I(f) = Re{ W*(f) · [X, Y, Z](f) }, integrated over 80–3000 Hz (below the array's spatial-aliasing region, above wind/handling rumble). Azimuth and elevation come from its direction; diffuseness is

ψ = 1 − 2‖⟨Re W*·v⟩‖ / ⟨|W|² + ‖v‖²⟩

which is 0 for a single plane wave and 1 for an ideally diffuse field. Directional statistics over time use circular means and the resultant length R (0 = no concentration, 1 = all energy from one bearing). Foreground/background splits use energy quartiles (loudest vs quietest 25 % of seconds).

Session descriptors (summarize)

Follows the conventions frozen for the Intercontinental-database reports so rows stay comparable across studies:

  • Leq, LAeq (energy means of the fast level), L10/L50/L90 exceedance percentiles, dynamics L10−L90;
  • events: fast level ≥ 8 dB above a running background (10th percentile in a sliding 60 s window) for ≥ 0.25 s — rate, count, median duration;
  • spectral centroid and flatness medians;
  • ψ median and IQR; energy-weighted mean azimuth and R; median foreground elevation.

Reading ψ and R together

High ψ + high R = diffuse but anisotropic (an airport hall that "leans" one way). Low ψ + high R = a point-source room (one running machine). Low R with any ψ = scattered sources. The two numbers do work neither does alone.

Spectral foreground (per-band background)

background.band_background runs a low-percentile filter per log band (default: 10th percentile over 300 s), from the cached 1 Hz logspec — no audio pass. On top of it:

  • foreground fraction — the share of total power sitting > 3 dB above the spectral background, per second (steady scenes score low even when loud; transient-dominated scenes score high even when quiet);
  • spectral events — connected time × band regions of ≥ 6 dB exceedance: band-limited events (a distant bell over traffic, a bird band, a beep) that the broadband ±8 dB detector never sees. Each carries onset, duration, band span, and peak rise.

analyze appends fg_fraction_median, fg_fraction_p90, spectral_events_per_min, and spectral_event_median_dur_s to the summary.

Modulation profile (modspec)

Environmental rhythm at three scales from cached envelopes: micro (0.5–20 Hz strike/speech-rate rhythm, from the 20 ms env_hi envelope), meso (0.01–0.5 Hz — traffic waves, surf), macro (duty cycles below 0.01 Hz). Per scale: a log-frequency modulation spectrum, the dominant modulation frequency and its prominence, and a band modulation depth; plus a windowed "rhythm spectrogram" of the session. Caches from extractor versions without env_hi fall back to the 8 Hz fast level (micro < 4 Hz).

Tonality and harmonicity (tonality)

From the per-minute mean PSD: prominent narrowband peaks are linked into tonal tracks (hums, bell partials, beeps — with duration and cents drift); a harmonic sieve finds the best f0 per minute and scores harmonicity (bells score low — their partial series is not harmonic); tonal energy folds onto a 12-bin pitch-class profile ("what key does the soundscape hum in").

Spatial dynamics (spatial)

Per-octave directness (|pseudo-intensity| / band power — the spatial analogue of foreground/background), pass-by detection (level events whose azimuth sweeps monotonically: moving sources with rate and direction), and the azimuth organization timeline R(t) — windowed, energy-weighted circular concentration of the direction of arrival.

Schedule matching (schedule)

Folds event streams at civic periods (minute, 5-min, quarter, half-hour, hour, day) and scores each with circular statistics. Read n_cycles before trusting a match: R is trivially 1 when all events fall inside one grid cycle. schedule.clock_offset turns an event of known wall-clock time into the clock_offset_s calibration value.

Event timbre templates (timbre)

Each spectral event gets a fingerprint — mel-band rise spectrum (what appeared) plus per-band decay slope (how it faded) — and fingerprints are clustered by correlation into recurring event classes: "the same sound again" across a session, transparent and corpus-comparable, no ML.

Masking (background.masking_index)

Floor elevation per band between a source-active and a quiet state: how much a dominant source hides the rest of the field, and in which bands. Often frequency-selective — the Haarlem bells elevate the typical floor 9–14 dB in their partial bands while the rest of the spectrum stays nearly free.

MIR views (music, optional)

With pip install "ambiscape[music]", ambiscape music renders the MIR-standard tempogram (onset autocorrelation in BPM, with librosa's octave-resolved global tempo) and chromagram — cross-checks for the built-in windowed-ACF tempogram and pitch-class profile.

Segment selection

pick_segments proposes representative windows — quietest, most active, typical, and (when a >6 dB state change exists) the transition — for listening, archiving, ISO indicators, or ambiviz rendering.