- AudioEvent: add speaker_id field (was on VoiceFrame only; needed on all events) - ToneEvent: add session_id field for session correlation across embedded consumers - README: full wire format documentation — JSON shape, field reference table, SSE envelope, Elcor mode subtext table, module license map - ToneEvent docstring references cf-core#40 as the wire format spec Closes cf-core#40
156 lines
5.3 KiB
Markdown
156 lines
5.3 KiB
Markdown
# cf-voice
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CircuitForge voice annotation pipeline. Produces `VoiceFrame` objects from a live audio stream — tone label, confidence, speaker identity, and shift magnitude — and exposes `ToneEvent` as the stable SSE wire type for downstream consumers (Linnet, Osprey, Falcon).
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**Status:** Notation v0.1.x — real inference pipeline live (faster-whisper STT, wav2vec2 SER, librosa prosody, pyannote diarization). Mock mode available for dev/CI without GPU or mic.
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## Install
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```bash
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# Mock mode only (no GPU required)
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pip install -e ../cf-voice
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# Real inference (STT + tone classifier + diarization)
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pip install -e "../cf-voice[inference]"
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```
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Copy `.env.example` to `.env` and fill in `HF_TOKEN` for diarization.
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## Quick start
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```python
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from cf_voice.context import ContextClassifier
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# Mock mode (no hardware needed)
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classifier = ContextClassifier.mock()
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async for frame in classifier.stream():
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print(frame.label, frame.confidence)
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# Real mic capture (requires [inference] extras + CF_VOICE_MOCK unset)
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classifier = ContextClassifier.from_env()
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async for frame in classifier.stream():
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print(frame.label, frame.confidence)
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```
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CLI smoke-test:
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```bash
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CF_VOICE_MOCK=1 cf-voice-demo
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```
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---
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## VoiceFrame
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Produced by `cf_voice.io` (audio capture layer). MIT licensed.
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```python
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@dataclass
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class VoiceFrame:
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label: str # tone descriptor, e.g. "Warmly impatient"
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confidence: float # 0.0–1.0
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speaker_id: str # ephemeral local label, e.g. "speaker_a"
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shift_magnitude: float # delta from previous frame, 0.0–1.0
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timestamp: float # session-relative seconds
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def is_reliable(self, threshold=0.6) -> bool: ...
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def is_shift(self, threshold=0.3) -> bool: ...
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```
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---
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## ToneEvent — SSE wire format
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`ToneEvent` is the stable SSE wire type emitted by Linnet's annotation stream
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and consumed by `<LinnetWidget />` embeds in Osprey, Falcon, and other products.
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**Field names are locked as of cf-voice v0.1.0** (cf-core#40).
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### JSON shape
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```json
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{
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"event_type": "tone",
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"timestamp": 4.82,
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"label": "Warmly impatient",
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"confidence": 0.79,
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"speaker_id": "speaker_a",
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"subtext": "Tone: Frustrated",
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"affect": "frustrated",
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"shift_magnitude": 0.74,
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"shift_direction": "more_urgent",
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"prosody_flags": ["fast_rate", "rising"],
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"session_id": "ses_abc123"
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}
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```
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### Field reference
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| Field | Type | Stable | Description |
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|---|---|---|---|
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| `event_type` | `"tone"` | yes | Always `"tone"` for ToneEvent |
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| `timestamp` | `float` | yes | Seconds since session start |
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| `label` | `str` | yes | Human-readable tone descriptor ("Warmly impatient") |
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| `confidence` | `float` | yes | 0.0–1.0. Below ~0.55 = speculative |
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| `speaker_id` | `str` | yes | Ephemeral diarization label ("speaker_a"). Resets per session |
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| `subtext` | `str \| null` | yes | Annotation text. Generic: `"Tone: Frustrated"`. Elcor: `"With barely concealed frustration:"` |
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| `affect` | `str` | yes | AFFECT_LABELS key ("frustrated"). See `cf_voice.events.AFFECT_LABELS` |
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| `shift_magnitude` | `float` | yes | 0.0–1.0. High = meaningful register change from previous frame |
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| `shift_direction` | `str` | yes | `"warmer"` \| `"colder"` \| `"more_urgent"` \| `"stable"` |
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| `prosody_flags` | `str[]` | no | Raw prosody signals ("fast_rate", "rising", "flat_pitch", "low_energy"). Subject to change |
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| `session_id` | `str` | yes | Caller-assigned. Correlates events to a conversation session |
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### SSE envelope
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Linnet emits events in standard SSE format:
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```
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event: tone-event
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data: {"event_type":"tone","timestamp":4.82,...}
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```
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Host apps subscribing via `<LinnetWidget />` receive `MessageEvent` with `type === "tone-event"`.
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### Elcor mode
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`subtext` switches format when the session is in Elcor mode (easter egg, unlocked by cumulative session time). Generic is always available; Elcor is opt-in via the session flag:
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| Affect | Generic | Elcor |
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|---|---|---|
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| frustrated | `Tone: Frustrated` | `With barely concealed frustration:` |
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| warm | `Tone: Warm` | `Warmly:` |
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| scripted | `Tone: Scripted` | `Reading from a script:` |
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| dismissive | `Tone: Dismissive` | `With polite dismissiveness:` |
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| tired | `Tone: Tired` | `With audible fatigue:` |
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---
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## Mock mode
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Set `CF_VOICE_MOCK=1` or pass `mock=True` to `make_io()`. Emits synthetic `VoiceFrame` objects on a timer. No GPU, microphone, or `HF_TOKEN` required. All API surface is identical to real mode.
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---
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## Module structure
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| Module | License | Purpose |
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|--------|---------|---------|
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| `cf_voice.models` | MIT | `VoiceFrame` dataclass |
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| `cf_voice.events` | MIT | `AudioEvent`, `ToneEvent`, wire format types |
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| `cf_voice.io` | MIT | `VoiceIO` base, `MockVoiceIO`, `make_io()` factory |
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| `cf_voice.capture` | BSL 1.1 | `MicVoiceIO` — real mic capture, 2s windowing |
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| `cf_voice.stt` | BSL 1.1 | `WhisperSTT` — faster-whisper async wrapper |
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| `cf_voice.classify` | BSL 1.1 | `ToneClassifier` — wav2vec2 SER + librosa prosody |
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| `cf_voice.diarize` | BSL 1.1 | `Diarizer` — pyannote.audio async wrapper |
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| `cf_voice.context` | BSL 1.1 | `ContextClassifier` — high-level consumer API |
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BSL applies to inference modules. IO + types + wire format = MIT.
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---
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## Consumed by
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- `Circuit-Forge/linnet` — real-time tone annotation PWA (primary consumer)
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- `Circuit-Forge/osprey` — telephony bridge voice context (Navigation v0.2.x)
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- `Circuit-Forge/falcon` (planned) — phone form-filling, IVR navigation
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