Mimir

Realtime cameras, microphones, chirplets, and field evidence organized into one coherent stream machine.

Audio Field

11 min read

Audio Field

Mimir’s audio field is six microphones, loopback/program reference, and two calibration speakers aligned into one presentation timeline.

Live Target

flowchart TD
    A["mic / loopback capture drivers"] --> B["Mimir.Runtime audio buffers"]
    C["speaker probe scheduler"] --> B
    B --> D["native alignment + phase state"]
    D --> E["Faust/native DSP"]
    E --> F["host voice"]
    E --> G["co-streamer voice"]
    E --> H["ambient / transients"]
    E --> I["loopback stems"]
    E --> J["spatial bed"]
    F --> K["OBS"]
    G --> K
    H --> K
    I --> K
    J --> K

Invariants

  • Scarlett speaker loopback is the timing authority when calibration chirplets are playing.
  • Focusrite dialogue mics are the voice anchors.
  • Camera mics are spatial/context witnesses.
  • Loopback/program audio is timing evidence where available; it outranks acoustic mics for clock/timing because it is the emitted program surface.
  • Distributed inputs must be aligned and resampled before they become program stems.
  • The five-second runtime window is allowed to be spent on alignment, resampling, separation, and spatial-field extraction. Low latency loses to a coherent volumetric sound field here.
  • Probe signals are budgeted telemetry, not a permanent audio bed.
  • Faust/native DSP owns the hot separation and spatialization graph.

Synchronization Modes

MimirAudioSynchronizationSettings.Mode is the runtime authority for what timing evidence Mimir is allowed to emit:

  • chirp-only: emit the deterministic calibration timeline and decode timing only from that active witness. This is the lab/debug mode and the fallback for silent program material.
  • passive: do not emit calibration audio. Use loopback/program audio as the timing witness by estimating delay between the loopback buffer and each mic buffer.
  • hybrid: prefer passive program-audio evidence when confidence is high, then emit a watermark when confidence falls. The passive side uses bounded GCC-PHAT-style phase correlation.

The mode belongs to the runtime, not the decoder. The decoder should consume known timing evidence; it should not decide whether Mimir is allowed to make sound.

The passive estimator is the first real program-audio path, not the final DSP actuator. It removes DC, pre-emphasizes the window, applies a Hann taper, runs a PHAT-weighted cross spectrum, and reports the strongest loopback-to-mic lag inside a bounded window. Positive delay still means the candidate mic is late relative to loopback. Negative lags are treated as contradictory passive evidence and carry zero confidence. A single passive window is also capped below certainty; full confidence belongs to repeated coherent state over time, not one attractive correlation peak.

The active calibration path is deliberately receiver-cheap in both chirp-only and hybrid. MimirBioacousticTimeline is the live runtime witness: it emits low-gain log-frequency words made from short formant-rich syllables, rhythm offsets, and speaker-specific variants. Acquisition is an energy proposal pass plus bounded motif matching; timeline placement comes from direct word identity, and a constrained local waveform correlation around the decoded delay provides the final fractional offset. The decoder keeps per-band response evidence for each detected motif so the same stream can calibrate timing and the speaker/room/mic transfer function.

MimirChirpBinTimeline remains as the older controlled calibration/reference artifact. Its full bin-energy surface and MimirChirpBinCalibrationModel still matter for measured usable bands, expected-symbol versus observed-bin confusion, timing residuals, delay hypotheses, phase summaries, and adaptive codebook plans. That evidence is allowed to shape the bioacoustic receiver next; it is not the active runtime sound.

The raw profile is kept even when a timing report is rejected, because a failed sync window can still teach us which bands survived the speaker/room/mic path. The receiver must consume persisted models to weight reliable symbols, downweight dead bands, apply phase-coherence weighting, apply first-order group-delay correction, and search joint global delay/frequency-shift hypotheses before selecting the coherent anchor path. If the measured path only leaves a smaller alphabet, Mimir should use that reliable symbol set and raise the sequence order so the timeline remains unique without pretending dead bands still carry code. The synthetic invariant is dotnet run --project .\src\Mimir.BufferSmoke\Mimir.BufferSmoke.csproj -- --bioacoustic-self-test; it renders the bioacoustic timeline, decodes direct word anchors, and requires a stable source clock. The standalone invariant is --standalone-bioacoustic-self-test --sample-rate 48000 --delay-samples 1269.5; it proves that a delayed receiver can recover canonical source time from the known codebook and schedule alone. --bioacoustic-cepstral-smoke proves the next receiver shape: degraded mel-cepstral calls are decoded through an augmented MFCC/projection-hash word index, not through dense waveform brute-force. chirp-only emits this witness continuously; hybrid still prefers passive program-audio evidence, then emits the low-gain bioacoustic witness only when passive confidence is weak. Default hybrid watermark gain is intentionally low (watermarkGain, or MIMIR_WATERMARK_GAIN).

Research notes:

Next Cut

The current diagnostic witness is native/probes/wasapi_audio_cadence, which emits timestamped WASAPI audio-block metadata into Mimir.Runtime through the frame-event adapter. It can request and verify specific shared or exclusive formats for device diagnosis, but it is not the Focusrite hot path. Scarlett capture belongs on ASIO so the runtime can use the interface clock and the 24-bit/192 kHz modes instead of the Windows shared engine. The probe has proven Focusrite mic, Kiyo Pro mic, Kiyo mic, both USB Camera / PS3 Eye mics, and Scarlett speaker loopback in rolling buffers when loopback audio is actively playing. One PS3 Eye mic previously enumerated but produced zero WASAPI packets until that Eye was unplugged and replugged.

native/probes/asio_audio_cadence is the first direct ASIO witness. It opens the registered Focusrite USB ASIO COM driver, reports channel counts, buffer size, sample-rate support, input sample type, and can run a short callback capture. With the Scarlett Solo 4th Gen attached to Starfire, Focusrite USB ASIO exposes 4 inputs and 2 outputs: Input 1, Input 2, Loopback 1, and Loopback 2. It accepts 44.1 through 192 kHz, reports a 192-frame preferred buffer, and captures nonzero 4-channel Int32LSB input callbacks at 192 kHz. Raven also has a loopback-capable Scarlett ASIO path at 192 kHz for co-streamer/game timing evidence, but Starfire owns the heavy local alignment, soundfield, and sensor-fusion work. The runtime hot path is now native/asio_capture plus MimirAsioStreamSource. The native DLL owns the Focusrite ASIO COM driver and keeps callback buffers in process; the managed source drains one 192 kHz Float32 block per ASIO input channel into Mimir.Runtime buffers (asio-ch0 through asio-ch3). The older --emit-json-blocks worker path remains a diagnostic probe, not the live Scarlett ingest path.

The probe also has a --monitor-sweep mode for measuring the acoustic ceiling. At 192 kHz, ASIO loopback detected emitted 8-40 kHz tones cleanly, but the current studio-monitor-to-Scarlett-mic acoustic path was already weak by 14-16 kHz and very weak above 20 kHz. Treat ultrasonic acoustic sync as unproven until a measured transducer/mic path earns it.

The active bioacoustic timing proof now runs in memory through the same runtime analyzer path. --bioacoustic-self-test proves direct word anchors, --standalone-bioacoustic-self-test --sample-rate 48000 --delay-samples 1269.5 proves a receiver can recover canonical source time from delayed audio alone, and --chirp-only-sync-self-test --sample-rate 48000 recovers a 317.375-sample delay with printed 0.000 us error using evidence=bioacoustic. --bioacoustic-cepstral-smoke runs an automated degradation panel over mel-cepstral warping and separable 5-tap blur; the current indexed MFCC decoder recovers word identity through the panel, while timing error remains a visible pressure for the global clock-hypothesis stage. The live ingest proof now feeds ASIO callbacks into Mimir.Runtime without a process/stdout bridge: a two-second BufferSmoke run at 192 kHz ingested more than 12,000 sample-bearing blocks and retained 2,048 blocks per channel across asio-ch0 through asio-ch3.

The full probe runtime config now enables sample-bearing blocks for every local audio source. MimirBioacousticTimeline owns the emitted calibration stream and the motif-matching shape used to analyze it. The default timeline is a deterministic set of self-identifying log-frequency words with separate left and right speaker variants. Any correctly detected word identifies the event index inside the current operating horizon, so a receiver can place its audio window on the canonical timeline without being handed Mimir’s runtime clock. Mimir queues half-second PCM segments ahead of the audio cursor. Each motif is a short phrase of formant-rich syllables with log-frequency contour and rhythm offsets, so the code is carried by both spectral shape and timing.

The intended decoder is a compact constrained song-contour transform, not a generic time-frequency explorer and not an outlier filter around bad guesses. Mimir owns the emitter, so the receiver keeps its ear open for known song words and maps each successful call directly to canonical time. A word is not a single scalar event: syllable onsets, bends, formants, rhythm offsets, payload ornaments, speaker tint, and log-mel contour all expose local time/frequency constraints. One call can pin a cluster of anchors at once. A decoded anchor means observed sample offset S corresponds to emitted event time T. A stream of anchors fits the source clock directly:

observed_sample = source_offset + canonical_seconds * effective_sample_rate

Delay and sampling-rate offset are derived by comparing the loopback clock fit to each mic clock fit over common canonical time. The state tracker is not allowed to launder invalid words into plausible timing. If a stream cannot produce at least one matched canonical song word, it has not decoded timing for that window. Reports carry rounded integer delay, fractional delay, and the count/confidence of contour anchors used to derive the report.

The same song starts the frequency-response path. Each active bioacoustic decode carries per-band and per-contour response evidence for the source set, whether or not each source earns a timing report. The older chirp-bin calibration model remains the controlled ASIO reference surface for response/confusion/delay captures: use Mimir.BufferSmoke --calibrate-chirp-bin-asio-f32 to render that reference timeline, optionally capture it through the ASIO worker with --capture-asio, compute the response/confusion/delay model, and persist it for decoder tuning.

MimirAudioSynchronizationStateTracker turns continuous observations into state. It confidence-gates reports, smooths fractional delay per source, and estimates delay slope as sampling-rate offset in ppm. This is the control input for the coming actuator. The state can survive a brief weak report, but it is not a license to run blind: loopback must keep receiving the emitted timeline or fresh reports will stop.

The actual Mimir app path now runs this online: MimirRuntime.Update keeps the bioacoustic timeline queued, polls sources, and updates sync analysis on a fixed cadence. MIMIR_SYNC_TELEMETRY_SECONDS enables console telemetry for live tests. Current runtime testing proves Fensalir output wakes the Scarlett loopback and the mic buffers stay live. The next failure is physical capture proof: the same canonical song-contour anchors need to stay stable through loopback, room mics, device clocks, and codec/network paths.

Retained Reference Calibration

flowchart TD
    A["MimirChirpletTimeline"] --> B["Fensalir audio output"]
    B --> C["Scarlett speaker loopback"]
    B --> D["room + speakers + mics"]
    C --> E["loopback rolling buffer"]
    D --> F["mic rolling buffers"]
    E --> G["matched reference traces"]
    F --> G
    G --> H["symbol likelihood events"]
    H --> L["timeline anchors"]
    L --> M["per-source clock fit"]
    M --> N["delay + SRO"]
    G --> I["per-source calibration profile"]
    N --> J["fractional delay / resampler actuator"]
    I --> K["frequency response normalization"]

The retained chirplet/chirp-bin timelines own three reference facts:

  • Emission: the PCM that Fensalir sends to the speakers.
  • Timing witness: the matched-filter atom bank used to find the stream in loopback and mic buffers.
  • Response witness: the per-band atoms used to measure how strongly each mic hears each emitted band.

Continuous active song evidence should give both the current delay and the drift/SRO by watching delay change over time. Per-band energy over the same stream gives the normalization curve. The important constraint is that all three measurements must be tied to the same emitted timeline, not three separately invented probes. The current ASIO artifact proves why this matters: Scarlett loopback channel 2 and loopback channel 3 both decode 12 anchors with 0.996 clock confidence, while physical input 1 decodes a noisier independent clock and a different strongest band set but still fails pairwise timing because no canonical events overlap the loopback path. That is not a blank failure anymore; it is calibration data for the next codebook/weighting cut.

The active symbol layer is now the song contour. It does not rely on one fixed frequency shelf or a coded sequence: syllable timing, contour bends, formants, payload ornaments, speaker tint, and local spectral flux all contribute so poor mic response does not erase the whole code. The old chirplet self-test remains available as historical proof of sub-frame math, but it must not retake authority over the active runtime path.

The older MimirChirpletTimeline matcher is a diagnostic/reference artifact, not the active runtime path. BuildChirpletEnergyTrace still behaves like a dense sliding matched-filter bank and should not retake authority.

Next, use the in-process ASIO source as the local Scarlett authority, prove stable acoustic anchors against real mics, then expose buffer depth, clock state, delay estimates, and stem routing in Fensalir UI. The analyzer accepts Float32, Int16, Int24, and Int32 PCM windows so direct driver paths can preserve real interface formats before Faust/native DSP owns the hot resampling and alignment.

Backlinks