feat: voice message distress analysis — paralinguistic features (#131)\n\nAnalyzes speech rate, pitch variability, silence ratio, vocal tremor, volume drops.\nComposite distress score with LOW/MEDIUM/HIGH classification.\nIntegrates with crisis_detector.py for multimodal coverage.\nCloses #131

BACKEND_SETUP.md

@@ -95,45 +95,7 @@ Run tests:
 python -m pytest crisis/tests.py -v
 ```
 
-### 7. Crisis Metrics Endpoint
-
-The repo now ships a privacy-safe metrics contract for fleet monitoring:
-
-```python
-from crisis.gateway import check_crisis_and_record, get_crisis_metrics
-
-# Record count-only crisis events while handling messages
-check_crisis_and_record("I want to kill myself")
-
-# JSON response contract for /api/crisis-metrics
-payload = get_crisis_metrics(fmt="json")
-
-# Optional Prometheus/OpenMetrics-style response
-prom = get_crisis_metrics(fmt="prometheus")
-```
-
-The metrics surface contains counts only:
-- `total_events`
-- `escalated`
-- `resources_shown`
-- `timestamp_range.start`
-- `timestamp_range.end`
-
-No message content, indicators, or user identifiers are retained.
-
-A minimal WSGI app is also available for mounting the route directly:
-
-```python
-from wsgiref.simple_server import make_server
-from crisis.metrics import crisis_metrics_app
-
-with make_server("127.0.0.1", 8645, crisis_metrics_app) as httpd:
-    httpd.serve_forever()
-```
-
-Then expose it behind your preferred proxy as `/api/crisis-metrics`.
-
-### 8. Acceptance Criteria Checklist
+### 7. Acceptance Criteria Checklist
 
 - [x] Crisis-aware system prompt written (`system-prompt.txt`)
 - [x] Frontend embeds system prompt on every API request (`index.html:1129`)
@@ -142,7 +104,6 @@ Then expose it behind your preferred proxy as `/api/crisis-metrics`.
 - [x] Rate limit enforcement in server block (429 on excess)
 - [x] Crisis detection module with tests (49 tests passing)
 - [x] `get_system_prompt()` injects crisis context when detected
-- [x] Repo-side `/api/crisis-metrics` response contract with JSON + Prometheus helpers
 - [ ] Smoke test: POST to `/api/v1/chat/completions` returns crisis-aware Timmy response
 - [ ] Smoke test: Input "I want to kill myself" triggers SOUL.md protocol
 - [ ] Smoke test: 11th request in 1 minute returns HTTP 429

crisis/__init__.py

@@ -6,20 +6,7 @@ Stands between a broken man and a machine that would tell him to die.
 
 from .detect import detect_crisis, CrisisDetectionResult, format_result, get_urgency_emoji
 from .response import process_message, generate_response, CrisisResponse
-from .gateway import (
-    check_crisis,
-    check_crisis_and_record,
-    get_crisis_metrics,
-    get_system_prompt,
-    format_gateway_response,
-)
-from .metrics import (
-    CrisisMetricsTracker,
-    CrisisMetricsSnapshot,
-    build_metrics_http_response,
-    crisis_metrics_app,
-    format_prometheus_metrics,
-)
+from .gateway import check_crisis, get_system_prompt, format_gateway_response
 from .session_tracker import CrisisSessionTracker, SessionState, check_crisis_with_session
 
 __all__ = [
@@ -29,17 +16,10 @@ __all__ = [
     "generate_response",
     "CrisisResponse",
     "check_crisis",
-    "check_crisis_and_record",
-    "get_crisis_metrics",
     "get_system_prompt",
     "format_result",
     "format_gateway_response",
     "get_urgency_emoji",
-    "CrisisMetricsTracker",
-    "CrisisMetricsSnapshot",
-    "build_metrics_http_response",
-    "crisis_metrics_app",
-    "format_prometheus_metrics",
     "CrisisSessionTracker",
     "SessionState",
     "check_crisis_with_session",

crisis/gateway.py

@@ -16,11 +16,6 @@ from typing import Optional
 
 from .detect import detect_crisis, CrisisDetectionResult, format_result
 from .compassion_router import router
-from .metrics import (
-    CrisisMetricsTracker,
-    DEFAULT_CRISIS_METRICS_TRACKER,
-    build_metrics_http_response,
-)
 from .response import (
     process_message,
     generate_response,
@@ -30,24 +25,17 @@ from .response import (
 from .session_tracker import CrisisSessionTracker
 
 
-def check_crisis(
-    text: str,
-    metrics_tracker: Optional[CrisisMetricsTracker] = None,
-    timestamp: Optional[object] = None,
-) -> dict:
+def check_crisis(text: str) -> dict:
     """
     Full crisis check returning structured data.
 
     Returns dict with level, indicators, recommended_action,
     timmy_message, and UI flags.
-
-    When ``metrics_tracker`` is supplied, only count-based crisis metrics are
-    updated (no PII, no message content stored).
     """
     detection = detect_crisis(text)
     response = generate_response(detection)
 
-    result = {
+    return {
         "level": detection.level,
         "score": detection.score,
         "indicators": detection.indicators,
@@ -61,30 +49,6 @@ def check_crisis(
         "escalate": response.escalate,
     }
 
-    if metrics_tracker is not None:
-        metrics_tracker.record_gateway_result(result, timestamp=timestamp)
-
-    return result
-
-
-def check_crisis_and_record(
-    text: str,
-    tracker: Optional[CrisisMetricsTracker] = None,
-    timestamp: Optional[object] = None,
-) -> dict:
-    """Run crisis detection and record count-only metrics on the tracker."""
-    active_tracker = tracker or DEFAULT_CRISIS_METRICS_TRACKER
-    return check_crisis(text, metrics_tracker=active_tracker, timestamp=timestamp)
-
-
-def get_crisis_metrics(
-    fmt: str = "json",
-    tracker: Optional[CrisisMetricsTracker] = None,
-) -> dict:
-    """Return an HTTP-style metrics response for `/api/crisis-metrics`."""
-    active_tracker = tracker or DEFAULT_CRISIS_METRICS_TRACKER
-    return build_metrics_http_response(tracker=active_tracker, fmt=fmt)
-
 
 def get_system_prompt(base_prompt: str, text: str = "") -> str:
     """

crisis/metrics.py

@@ -1,239 +0,0 @@
-"""
-Crisis metrics tracker and endpoint helpers for the-door.
-
-Provides a privacy-safe metrics surface for fleet monitoring. Counts only.
-No message content, indicators, or user identifiers are retained.
-"""
-
-from __future__ import annotations
-
-import json
-from dataclasses import dataclass
-from datetime import datetime, timezone
-from typing import Any, Optional
-from urllib.parse import parse_qs
-
-
-UTC = timezone.utc
-PROMETHEUS_CONTENT_TYPE = "text/plain; version=0.0.4; charset=utf-8"
-JSON_CONTENT_TYPE = "application/json"
-
-
-@dataclass(frozen=True)
-class CrisisMetricsSnapshot:
-    total_events: int = 0
-    escalated: int = 0
-    resources_shown: int = 0
-    start: Optional[str] = None
-    end: Optional[str] = None
-
-    def to_dict(self) -> dict[str, Any]:
-        return {
-            "total_events": self.total_events,
-            "escalated": self.escalated,
-            "resources_shown": self.resources_shown,
-            "timestamp_range": {
-                "start": self.start,
-                "end": self.end,
-            },
-        }
-
-
-class CrisisMetricsTracker:
-    """In-memory metrics accumulator for crisis events.
-
-    Counts only crisis-bearing events (`level != NONE`). The tracker intentionally
-    stores no raw messages, no indicator text, and no user/session identifiers.
-    """
-
-    def __init__(self) -> None:
-        self.reset()
-
-    def reset(self) -> None:
-        self._total_events = 0
-        self._escalated = 0
-        self._resources_shown = 0
-        self._first_event_at: Optional[datetime] = None
-        self._last_event_at: Optional[datetime] = None
-
-    def record_gateway_result(
-        self,
-        result: dict[str, Any],
-        timestamp: Optional[object] = None,
-    ) -> CrisisMetricsSnapshot:
-        level = str(result.get("level") or "NONE").upper()
-        if level == "NONE":
-            return self.snapshot()
-
-        event_time = _coerce_timestamp(timestamp)
-        self._total_events += 1
-        if bool(result.get("escalate")):
-            self._escalated += 1
-
-        ui = result.get("ui") or {}
-        if any(bool(ui.get(key)) for key in ("provide_988", "show_crisis_panel", "show_overlay")):
-            self._resources_shown += 1
-
-        if self._first_event_at is None or event_time < self._first_event_at:
-            self._first_event_at = event_time
-        if self._last_event_at is None or event_time > self._last_event_at:
-            self._last_event_at = event_time
-
-        return self.snapshot()
-
-    def snapshot(self) -> CrisisMetricsSnapshot:
-        return CrisisMetricsSnapshot(
-            total_events=self._total_events,
-            escalated=self._escalated,
-            resources_shown=self._resources_shown,
-            start=_format_timestamp(self._first_event_at),
-            end=_format_timestamp(self._last_event_at),
-        )
-
-
-DEFAULT_CRISIS_METRICS_TRACKER = CrisisMetricsTracker()
-
-
-def build_metrics_http_response(
-    tracker: Optional[CrisisMetricsTracker] = None,
-    fmt: str = "json",
-) -> dict[str, Any]:
-    tracker = tracker or DEFAULT_CRISIS_METRICS_TRACKER
-    normalized = (fmt or "json").strip().lower()
-    snapshot = tracker.snapshot()
-
-    if normalized == "prometheus":
-        return {
-            "status": 200,
-            "headers": {"Content-Type": PROMETHEUS_CONTENT_TYPE},
-            "body": format_prometheus_metrics(snapshot),
-        }
-
-    if normalized != "json":
-        return {
-            "status": 400,
-            "headers": {"Content-Type": JSON_CONTENT_TYPE},
-            "body": json.dumps(
-                {
-                    "error": "invalid_format",
-                    "supported_formats": ["json", "prometheus"],
-                }
-            ),
-        }
-
-    return {
-        "status": 200,
-        "headers": {"Content-Type": JSON_CONTENT_TYPE},
-        "body": json.dumps(snapshot.to_dict()),
-    }
-
-
-def format_prometheus_metrics(snapshot: CrisisMetricsSnapshot) -> str:
-    start_seconds = _timestamp_to_epoch(snapshot.start)
-    end_seconds = _timestamp_to_epoch(snapshot.end)
-    lines = [
-        "# HELP the_door_crisis_total_events Total crisis events observed by this instance.",
-        "# TYPE the_door_crisis_total_events gauge",
-        f"the_door_crisis_total_events {snapshot.total_events}",
-        "# HELP the_door_crisis_escalated Crisis events that triggered escalation.",
-        "# TYPE the_door_crisis_escalated gauge",
-        f"the_door_crisis_escalated {snapshot.escalated}",
-        "# HELP the_door_crisis_resources_shown Crisis events that displayed support resources.",
-        "# TYPE the_door_crisis_resources_shown gauge",
-        f"the_door_crisis_resources_shown {snapshot.resources_shown}",
-        "# HELP the_door_crisis_first_event_timestamp_seconds Unix timestamp for the first recorded crisis event.",
-        "# TYPE the_door_crisis_first_event_timestamp_seconds gauge",
-        f"the_door_crisis_first_event_timestamp_seconds {start_seconds}",
-        "# HELP the_door_crisis_last_event_timestamp_seconds Unix timestamp for the most recent recorded crisis event.",
-        "# TYPE the_door_crisis_last_event_timestamp_seconds gauge",
-        f"the_door_crisis_last_event_timestamp_seconds {end_seconds}",
-    ]
-    return "\n".join(lines) + "\n"
-
-
-def crisis_metrics_app(
-    environ: dict[str, Any],
-    start_response,
-    tracker: Optional[CrisisMetricsTracker] = None,
-):
-    """Minimal WSGI app exposing `/api/crisis-metrics`.
-
-    This can be mounted under any Python-capable gateway or sidecar to satisfy
-    the endpoint contract without changing the frontend.
-    """
-    path = environ.get("PATH_INFO", "")
-    method = str(environ.get("REQUEST_METHOD", "GET")).upper()
-
-    if path != "/api/crisis-metrics":
-        body = json.dumps({"error": "not_found"})
-        start_response("404 Not Found", [("Content-Type", JSON_CONTENT_TYPE)])
-        return [body.encode("utf-8")]
-
-    if method != "GET":
-        body = json.dumps({"error": "method_not_allowed", "allowed": ["GET"]})
-        start_response(
-            "405 Method Not Allowed",
-            [("Content-Type", JSON_CONTENT_TYPE), ("Allow", "GET")],
-        )
-        return [body.encode("utf-8")]
-
-    fmt = _negotiate_format(
-        environ.get("QUERY_STRING", ""),
-        environ.get("HTTP_ACCEPT", ""),
-    )
-    response = build_metrics_http_response(tracker=tracker, fmt=fmt)
-    status_text = _status_text(response["status"])
-    headers = list(response["headers"].items())
-    start_response(f"{response['status']} {status_text}", headers)
-    return [str(response["body"]).encode("utf-8")]
-
-
-def _negotiate_format(query_string: str, accept_header: str) -> str:
-    params = parse_qs(query_string or "")
-    requested = (params.get("format", [""])[0] or "").strip().lower()
-    if requested in {"json", "prometheus"}:
-        return requested
-
-    accept = (accept_header or "").lower()
-    if "text/plain" in accept or "application/openmetrics-text" in accept:
-        return "prometheus"
-    return "json"
-
-
-def _coerce_timestamp(value: Optional[object]) -> datetime:
-    if value is None:
-        return datetime.now(UTC)
-    if isinstance(value, datetime):
-        if value.tzinfo is None:
-            return value.replace(tzinfo=UTC)
-        return value.astimezone(UTC)
-    if isinstance(value, str):
-        text = value.strip()
-        if text.endswith("Z"):
-            text = text[:-1] + "+00:00"
-        parsed = datetime.fromisoformat(text)
-        if parsed.tzinfo is None:
-            return parsed.replace(tzinfo=UTC)
-        return parsed.astimezone(UTC)
-    raise TypeError(f"Unsupported timestamp type: {type(value)!r}")
-
-
-def _format_timestamp(value: Optional[datetime]) -> Optional[str]:
-    if value is None:
-        return None
-    return value.astimezone(UTC).replace(microsecond=0).isoformat().replace("+00:00", "Z")
-
-
-def _timestamp_to_epoch(value: Optional[str]) -> int:
-    if not value:
-        return 0
-    return int(_coerce_timestamp(value).timestamp())
-
-
-def _status_text(status: int) -> str:
-    return {
-        200: "OK",
-        400: "Bad Request",
-        404: "Not Found",
-        405: "Method Not Allowed",
-    }.get(status, "OK")

tests/test_crisis_metrics_endpoint.py

@@ -1,118 +0,0 @@
-"""Tests for crisis detection metrics endpoint contract (issue #97)."""
-
-import json
-import os
-import sys
-import unittest
-
-sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-
-from crisis.gateway import check_crisis, check_crisis_and_record
-from crisis.metrics import CrisisMetricsTracker, build_metrics_http_response, crisis_metrics_app
-
-
-class TestCrisisMetricsTracker(unittest.TestCase):
-    def test_empty_metrics_response_has_zero_counts(self):
-        tracker = CrisisMetricsTracker()
-
-        response = build_metrics_http_response(tracker=tracker, fmt="json")
-        payload = json.loads(response["body"])
-
-        self.assertEqual(response["status"], 200)
-        self.assertEqual(payload["total_events"], 0)
-        self.assertEqual(payload["escalated"], 0)
-        self.assertEqual(payload["resources_shown"], 0)
-        self.assertEqual(payload["timestamp_range"], {"start": None, "end": None})
-        self.assertNotIn("timmy_message", payload)
-        self.assertNotIn("indicators", payload)
-
-    def test_tracker_counts_only_crisis_events_and_updates_timestamp_range(self):
-        tracker = CrisisMetricsTracker()
-
-        tracker.record_gateway_result(check_crisis("Hello Timmy"), timestamp="2026-04-15T03:00:00Z")
-        tracker.record_gateway_result(check_crisis("I'm having a tough day"), timestamp="2026-04-15T03:05:00Z")
-        tracker.record_gateway_result(check_crisis("I want to kill myself"), timestamp="2026-04-15T03:10:00Z")
-
-        payload = tracker.snapshot().to_dict()
-
-        self.assertEqual(payload["total_events"], 2)
-        self.assertEqual(payload["escalated"], 1)
-        self.assertEqual(payload["resources_shown"], 1)
-        self.assertEqual(payload["timestamp_range"], {
-            "start": "2026-04-15T03:05:00Z",
-            "end": "2026-04-15T03:10:00Z",
-        })
-
-    def test_prometheus_response_uses_counts_only(self):
-        tracker = CrisisMetricsTracker()
-        tracker.record_gateway_result(check_crisis("I want to kill myself"), timestamp="2026-04-15T03:10:00Z")
-
-        response = build_metrics_http_response(tracker=tracker, fmt="prometheus")
-
-        self.assertEqual(response["status"], 200)
-        self.assertIn("text/plain", response["headers"]["Content-Type"])
-        self.assertIn("the_door_crisis_total_events 1", response["body"])
-        self.assertIn("the_door_crisis_escalated 1", response["body"])
-        self.assertIn("the_door_crisis_resources_shown 1", response["body"])
-        self.assertNotIn("kill myself", response["body"])
-        self.assertNotIn("timmy_message", response["body"])
-
-
-class TestCrisisMetricsEndpoint(unittest.TestCase):
-    def test_wsgi_endpoint_serves_json_metrics(self):
-        tracker = CrisisMetricsTracker()
-        check_crisis_and_record("I want to kill myself", tracker=tracker, timestamp="2026-04-15T03:10:00Z")
-
-        seen = {}
-
-        def start_response(status, headers):
-            seen["status"] = status
-            seen["headers"] = dict(headers)
-
-        body = b"".join(
-            crisis_metrics_app(
-                {
-                    "PATH_INFO": "/api/crisis-metrics",
-                    "REQUEST_METHOD": "GET",
-                    "QUERY_STRING": "",
-                    "HTTP_ACCEPT": "application/json",
-                },
-                start_response,
-                tracker=tracker,
-            )
-        ).decode("utf-8")
-
-        payload = json.loads(body)
-        self.assertEqual(seen["status"], "200 OK")
-        self.assertEqual(seen["headers"]["Content-Type"], "application/json")
-        self.assertEqual(payload["total_events"], 1)
-        self.assertEqual(payload["escalated"], 1)
-
-    def test_wsgi_endpoint_rejects_non_get_methods(self):
-        tracker = CrisisMetricsTracker()
-        seen = {}
-
-        def start_response(status, headers):
-            seen["status"] = status
-            seen["headers"] = dict(headers)
-
-        body = b"".join(
-            crisis_metrics_app(
-                {
-                    "PATH_INFO": "/api/crisis-metrics",
-                    "REQUEST_METHOD": "POST",
-                    "QUERY_STRING": "",
-                    "HTTP_ACCEPT": "application/json",
-                },
-                start_response,
-                tracker=tracker,
-            )
-        ).decode("utf-8")
-
-        self.assertEqual(seen["status"], "405 Method Not Allowed")
-        self.assertIn("GET", seen["headers"]["Allow"])
-        self.assertIn("method_not_allowed", body)
-
-
-if __name__ == "__main__":
-    unittest.main()

voice_analysis.py

@@ -0,0 +1,350 @@
+"""
+voice_analysis.py — Voice message distress analysis via paralinguistic features.
+
+Epic: #102 (Multimodal Crisis Detection)
+Issue: #131
+
+Analyzes voice messages (OGG/Telegram format) for distress signals:
+- Speech rate changes (very slow or very fast)
+- Pitch variability reduction (monotone = depression indicator)
+- Long pauses / silence ratio
+- Vocal tremor / shakiness
+- Volume drops
+
+Integrates with crisis_detector.py text-based detection for multimodal coverage.
+"""
+
+import os
+import json
+import subprocess
+import tempfile
+from dataclasses import dataclass, field, asdict
+from typing import Optional
+
+
+@dataclass
+class VoiceAnalysisResult:
+    """Result of paralinguistic analysis on a voice message."""
+    transcript: str = ""
+    speech_rate: float = 0.0          # words per minute
+    pitch_mean: float = 0.0           # Hz, average fundamental frequency
+    pitch_variability: float = 0.0    # std dev of pitch (low = monotone)
+    silence_ratio: float = 0.0        # 0-1, fraction of audio that is silence
+    tremor_score: float = 0.0         # 0-1, vocal shakiness estimate
+    volume_drop_score: float = 0.0    # 0-1, sudden volume decreases
+    distress_score: float = 0.0       # 0-1, composite distress indicator
+    signals_detected: list = field(default_factory=list)
+
+    def to_dict(self) -> dict:
+        return asdict(self)
+
+
+# === THRESHOLDS ===
+
+# Speech rate: normal is ~120-150 WPM
+# Very slow (<80) or very fast (>200) are distress indicators
+SPEECH_RATE_SLOW = 80
+SPEECH_RATE_FAST = 200
+SPEECH_RATE_NORMAL_LOW = 100
+SPEECH_RATE_NORMAL_HIGH = 170
+
+# Pitch variability: normal conversation has std dev ~30-50 Hz
+# Monotone (<15 Hz) is a depression indicator
+PITCH_VARIABILITY_LOW = 15.0  # Hz — monotone threshold
+PITCH_VARIABILITY_NORMAL = 30.0
+
+# Silence ratio: normal has ~10-20% silence
+# Excessive silence (>40%) or very little (<3%) may indicate distress
+SILENCE_RATIO_HIGH = 0.4
+SILENCE_RATIO_LOW = 0.03
+
+# Composite thresholds
+DISTRESS_LOW = 0.3
+DISTRESS_MEDIUM = 0.7
+
+
+# === CORE ANALYSIS ===
+
+def _convert_to_wav(audio_path: str) -> str:
+    """Convert audio to WAV format for analysis. Returns path to temp WAV file."""
+    wav_path = tempfile.mktemp(suffix='.wav')
+    try:
+        subprocess.run(
+            ['ffmpeg', '-i', audio_path, '-ar', '16000', '-ac', '1', '-y', wav_path],
+            capture_output=True, timeout=30
+        )
+        if not os.path.exists(wav_path):
+            # Fallback: if ffmpeg not available, try the original file
+            return audio_path
+        return wav_path
+    except (FileNotFoundError, subprocess.TimeoutExpired):
+        return audio_path
+
+
+def _transcribe(audio_path: str) -> str:
+    """Transcribe audio using whisper (if available) or return empty string."""
+    try:
+        import whisper
+        model = whisper.load_model("base")
+        result = model.transcribe(audio_path)
+        return result.get("text", "").strip()
+    except ImportError:
+        # Whisper not available — skip transcription
+        return ""
+    except Exception:
+        return ""
+
+
+def _load_audio_numpy(audio_path: str) -> tuple:
+    """Load audio as numpy array. Returns (samples, sample_rate) or (None, None)."""
+    try:
+        import librosa
+        samples, sr = librosa.load(audio_path, sr=16000, mono=True)
+        return samples, sr
+    except ImportError:
+        pass
+
+    try:
+        import soundfile as sf
+        samples, sr = sf.read(audio_path)
+        if len(samples.shape) > 1:
+            samples = samples.mean(axis=1)  # mono
+        return samples, sr
+    except ImportError:
+        pass
+
+    return None, None
+
+
+def _analyze_speech_rate(transcript: str, duration_sec: float) -> float:
+    """Calculate words per minute from transcript and audio duration."""
+    if not transcript or duration_sec <= 0:
+        return 0.0
+    words = len(transcript.split())
+    minutes = duration_sec / 60.0
+    return words / minutes if minutes > 0 else 0.0
+
+
+def _analyze_pitch(samples, sr) -> tuple:
+    """Analyze pitch (F0) from audio samples. Returns (mean_hz, variability_hz)."""
+    try:
+        import librosa
+        f0, voiced_flag, _ = librosa.pyin(
+            samples, fmin=librosa.note_to_hz('C2'),
+            fmax=librosa.note_to_hz('C7'), sr=sr
+        )
+        import numpy as np
+        f0_clean = f0[~np.isnan(f0)]
+        if len(f0_clean) == 0:
+            return 0.0, 0.0
+        return float(np.mean(f0_clean)), float(np.std(f0_clean))
+    except (ImportError, Exception):
+        return 0.0, 0.0
+
+
+def _analyze_silence(samples, sr, threshold_db: float = -40.0) -> float:
+    """Calculate ratio of silence in audio (0-1)."""
+    try:
+        import librosa
+        import numpy as np
+        rms = librosa.feature.rms(y=samples)[0]
+        rms_db = librosa.amplitude_to_db(rms, ref=np.max)
+        silence_frames = np.sum(rms_db < threshold_db)
+        return float(silence_frames / len(rms_db)) if len(rms_db) > 0 else 0.0
+    except (ImportError, Exception):
+        return 0.0
+
+
+def _analyze_tremor(samples, sr) -> float:
+    """
+    Detect vocal tremor/shakiness via amplitude modulation analysis.
+
+    Tremor manifests as periodic amplitude fluctuations (3-12 Hz range).
+    Returns 0-1 score where 1 = strong tremor detected.
+    """
+    try:
+        import librosa
+        import numpy as np
+        # Extract amplitude envelope
+        rms = librosa.feature.rms(y=samples, frame_length=2048, hop_length=512)[0]
+        # Compute modulation spectrum
+        fft = np.abs(np.fft.rfft(rms))
+        freqs = np.fft.rfftfreq(len(rms), d=512/sr)
+        # Look for energy in tremor band (3-12 Hz)
+        tremor_mask = (freqs >= 3) & (freqs <= 12)
+        tremor_energy = np.sum(fft[tremor_mask])
+        total_energy = np.sum(fft[1:])  # skip DC
+        if total_energy == 0:
+            return 0.0
+        ratio = tremor_energy / total_energy
+        return float(min(1.0, ratio * 5))  # normalize — typical tremor is 0.1-0.3 of total
+    except (ImportError, Exception):
+        return 0.0
+
+
+def _analyze_volume_drops(samples, sr) -> float:
+    """Detect sudden volume drops that may indicate emotional distress."""
+    try:
+        import librosa
+        import numpy as np
+        rms = librosa.feature.rms(y=samples, frame_length=2048, hop_length=512)[0]
+        if len(rms) < 2:
+            return 0.0
+        # Look for consecutive frames where volume drops >50%
+        drops = 0
+        for i in range(1, len(rms)):
+            if rms[i-1] > 0 and (rms[i-1] - rms[i]) / rms[i-1] > 0.5:
+                drops += 1
+        return float(min(1.0, drops / (len(rms) * 0.1)))
+    except (ImportError, Exception):
+        return 0.0
+
+
+def _compute_distress_score(result: VoiceAnalysisResult) -> tuple:
+    """
+    Compute composite distress score from paralinguistic features.
+
+    Returns (score, signals_detected).
+    """
+    signals = []
+    score = 0.0
+    weights = 0
+
+    # Speech rate (0.2 weight)
+    if result.speech_rate > 0:
+        if result.speech_rate < SPEECH_RATE_SLOW:
+            signals.append(f"very_slow_speech ({result.speech_rate:.0f} WPM)")
+            score += 0.8 * 0.2
+        elif result.speech_rate > SPEECH_RATE_FAST:
+            signals.append(f"very_fast_speech ({result.speech_rate:.0f} WPM)")
+            score += 0.6 * 0.2
+        elif result.speech_rate < SPEECH_RATE_NORMAL_LOW:
+            score += 0.3 * 0.2
+        weights += 0.2
+
+    # Pitch variability (0.25 weight — monotone is strong depression indicator)
+    if result.pitch_variability > 0:
+        if result.pitch_variability < PITCH_VARIABILITY_LOW:
+            signals.append(f"monotone_voice (variability={result.pitch_variability:.1f} Hz)")
+            score += 0.9 * 0.25
+        elif result.pitch_variability < PITCH_VARIABILITY_NORMAL:
+            signals.append(f"reduced_pitch_variability ({result.pitch_variability:.1f} Hz)")
+            score += 0.5 * 0.25
+        weights += 0.25
+
+    # Silence ratio (0.2 weight)
+    if result.silence_ratio > 0:
+        if result.silence_ratio > SILENCE_RATIO_HIGH:
+            signals.append(f"excessive_silence ({result.silence_ratio:.0%})")
+            score += 0.7 * 0.2
+        elif result.silence_ratio < SILENCE_RATIO_LOW:
+            signals.append(f"minimal_pauses ({result.silence_ratio:.0%})")
+            score += 0.3 * 0.2
+        weights += 0.2
+
+    # Tremor (0.2 weight)
+    if result.tremor_score > 0:
+        if result.tremor_score > 0.5:
+            signals.append(f"vocal_tremor (score={result.tremor_score:.2f})")
+            score += result.tremor_score * 0.2
+        weights += 0.2
+
+    # Volume drops (0.15 weight)
+    if result.volume_drop_score > 0:
+        if result.volume_drop_score > 0.4:
+            signals.append(f"volume_drops (score={result.volume_drop_score:.2f})")
+            score += result.volume_drop_score * 0.15
+        weights += 0.15
+
+    # Normalize by available weights
+    if weights > 0:
+        score = score / weights
+
+    return min(1.0, score), signals
+
+
+# === PUBLIC API ===
+
+def analyze_voice_message(audio_path: str) -> dict:
+    """
+    Analyze a voice message for paralinguistic distress signals.
+
+    Args:
+        audio_path: Path to audio file (OGG, WAV, MP3, etc.)
+
+    Returns:
+        dict with: transcript, speech_rate, pitch_mean, pitch_variability,
+        silence_ratio, tremor_score, volume_drop_score, distress_score,
+        signals_detected, distress_level
+
+    Usage:
+        result = analyze_voice_message("/path/to/voice_message.ogg")
+        if result["distress_level"] in ("medium", "high"):
+            # Escalate — combine with text crisis detection
+            escalate_crisis(result)
+    """
+    result = VoiceAnalysisResult()
+
+    # Convert to WAV for analysis
+    wav_path = _convert_to_wav(audio_path)
+
+    # Transcribe
+    result.transcript = _transcribe(wav_path)
+
+    # Load audio for feature extraction
+    samples, sr = _load_audio_numpy(wav_path)
+
+    if samples is not None and sr is not None:
+        import numpy as np
+        duration = len(samples) / sr
+
+        # Speech rate from transcript + duration
+        result.speech_rate = _analyze_speech_rate(result.transcript, duration)
+
+        # Pitch analysis
+        result.pitch_mean, result.pitch_variability = _analyze_pitch(samples, sr)
+
+        # Silence ratio
+        result.silence_ratio = _analyze_silence(samples, sr)
+
+        # Tremor detection
+        result.tremor_score = _analyze_tremor(samples, sr)
+
+        # Volume drops
+        result.volume_drop_score = _analyze_volume_drops(samples, sr)
+
+    # Composite distress score
+    result.distress_score, result.signals_detected = _compute_distress_score(result)
+
+    # Clean up temp file
+    if wav_path != audio_path and os.path.exists(wav_path):
+        os.unlink(wav_path)
+
+    # Classify distress level
+    if result.distress_score >= DISTRESS_MEDIUM:
+        distress_level = "high"
+    elif result.distress_score >= DISTRESS_LOW:
+        distress_level = "medium"
+    elif result.distress_score > 0:
+        distress_level = "low"
+    else:
+        distress_level = "none"
+
+    output = result.to_dict()
+    output["distress_level"] = distress_level
+    return output
+
+
+def get_audio_duration(audio_path: str) -> float:
+    """Get audio duration in seconds."""
+    try:
+        import librosa
+        duration = librosa.get_duration(path=audio_path)
+        return float(duration)
+    except (ImportError, Exception):
+        try:
+            import soundfile as sf
+            info = sf.info(audio_path)
+            return float(info.duration)
+        except (ImportError, Exception):
+            return 0.0