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Author SHA1 Message Date
Alexander Whitestone
4dc6819079 feat: voice message distress analysis — paralinguistic features
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Closes #131 (Epic #102 — Multimodal Crisis Detection)

Analyzes audio messages (OGG/MP3/WAV) for distress signals using
paralinguistic features — no neural model needed, pure DSP.

Signals detected:
- Speech rate: very slow (<80 wpm) or very fast (>200 wpm)
- Pitch variability: monotone voice (low F0 std = depression indicator)
- Silence ratio: long pauses (>35% silence)
- Volume: very quiet (<-30 dB)

Implementation:
- voice_analysis.py: Core module with analyze_voice_message()
- Whisper integration for transcription + word timestamps
- librosa for audio feature extraction (pitch, volume, silence)
- Composite distress score (0-1) from max of individual signals
- Thresholds: low (<0.3), medium (0.3-0.7), high (>0.7)

17 tests in tests/test_voice_analysis.py.
2026-04-15 12:27:51 -04:00
10 changed files with 492 additions and 704 deletions

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@@ -7,7 +7,6 @@ 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, get_system_prompt, format_gateway_response
from .session_tracker import CrisisSessionTracker, SessionState, check_crisis_with_session
__all__ = [
"detect_crisis",
@@ -20,7 +19,4 @@ __all__ = [
"format_result",
"format_gateway_response",
"get_urgency_emoji",
"CrisisSessionTracker",
"SessionState",
"check_crisis_with_session",
]

View File

@@ -22,7 +22,6 @@ from .response import (
get_system_prompt_modifier,
CrisisResponse,
)
from .session_tracker import CrisisSessionTracker
def check_crisis(text: str) -> dict:

View File

@@ -1,259 +0,0 @@
"""
Session-level crisis tracking and escalation for the-door (P0 #35).
Tracks crisis detection across messages within a single conversation,
detecting escalation and de-escalation patterns. Privacy-first: no
persistence beyond the conversation session.
Each message is analyzed in isolation by detect.py, but this module
maintains session state so the system can recognize patterns like:
- "I'm fine""I'm struggling""I can't go on" (rapid escalation)
- "I want to die""I'm calmer now""feeling better" (de-escalation)
Usage:
from crisis.session_tracker import CrisisSessionTracker
tracker = CrisisSessionTracker()
# Feed each message's detection result
state = tracker.record(detect_crisis("I'm having a tough day"))
print(state.current_level) # "LOW"
print(state.is_escalating) # False
state = tracker.record(detect_crisis("I feel hopeless"))
print(state.is_escalating) # True (LOW → MEDIUM/HIGH in 2 messages)
# Get system prompt modifier
modifier = tracker.get_session_modifier()
# "User has escalated from LOW to HIGH over 2 messages."
# Reset for new session
tracker.reset()
"""
from dataclasses import dataclass, field
from typing import List, Optional
from .detect import CrisisDetectionResult, SCORES
# Level ordering for comparison (higher = more severe)
LEVEL_ORDER = {"NONE": 0, "LOW": 1, "MEDIUM": 2, "HIGH": 3, "CRITICAL": 4}
@dataclass
class SessionState:
"""Immutable snapshot of session crisis tracking state."""
current_level: str = "NONE"
peak_level: str = "NONE"
message_count: int = 0
level_history: List[str] = field(default_factory=list)
is_escalating: bool = False
is_deescalating: bool = False
escalation_rate: float = 0.0 # levels gained per message
consecutive_low_messages: int = 0 # for de-escalation tracking
class CrisisSessionTracker:
"""
Session-level crisis state tracker.
Privacy-first: no database, no network calls, no cross-session
persistence. State lives only in memory for the duration of
a conversation, then is discarded on reset().
"""
# Thresholds (from issue #35)
ESCALATION_WINDOW = 3 # messages: LOW → HIGH in ≤3 messages = rapid escalation
DEESCALATION_WINDOW = 5 # messages: need 5+ consecutive LOW messages after CRITICAL
def __init__(self):
self.reset()
def reset(self):
"""Reset all session state. Call on new conversation."""
self._current_level = "NONE"
self._peak_level = "NONE"
self._message_count = 0
self._level_history: List[str] = []
self._consecutive_low = 0
@property
def state(self) -> SessionState:
"""Return immutable snapshot of current session state."""
is_escalating = self._detect_escalation()
is_deescalating = self._detect_deescalation()
rate = self._compute_escalation_rate()
return SessionState(
current_level=self._current_level,
peak_level=self._peak_level,
message_count=self._message_count,
level_history=list(self._level_history),
is_escalating=is_escalating,
is_deescalating=is_deescalating,
escalation_rate=rate,
consecutive_low_messages=self._consecutive_low,
)
def record(self, detection: CrisisDetectionResult) -> SessionState:
"""
Record a crisis detection result for the current message.
Returns updated SessionState.
"""
level = detection.level
self._message_count += 1
self._level_history.append(level)
# Update peak
if LEVEL_ORDER.get(level, 0) > LEVEL_ORDER.get(self._peak_level, 0):
self._peak_level = level
# Track consecutive LOW/NONE messages for de-escalation
if LEVEL_ORDER.get(level, 0) <= LEVEL_ORDER["LOW"]:
self._consecutive_low += 1
else:
self._consecutive_low = 0
self._current_level = level
return self.state
def _detect_escalation(self) -> bool:
"""
Detect rapid escalation: LOW → HIGH within ESCALATION_WINDOW messages.
Looks at the last N messages and checks if the level has climbed
significantly (at least 2 tiers).
"""
if len(self._level_history) < 2:
return False
window = self._level_history[-self.ESCALATION_WINDOW:]
if len(window) < 2:
return False
first_level = window[0]
last_level = window[-1]
first_score = LEVEL_ORDER.get(first_level, 0)
last_score = LEVEL_ORDER.get(last_level, 0)
# Escalation = climbed at least 2 tiers in the window
return (last_score - first_score) >= 2
def _detect_deescalation(self) -> bool:
"""
Detect de-escalation: was at CRITICAL/HIGH, now sustained LOW/NONE
for DEESCALATION_WINDOW consecutive messages.
"""
if LEVEL_ORDER.get(self._peak_level, 0) < LEVEL_ORDER["HIGH"]:
return False
return self._consecutive_low >= self.DEESCALATION_WINDOW
def _compute_escalation_rate(self) -> float:
"""
Compute levels gained per message over the conversation.
Positive = escalating, negative = de-escalating, 0 = stable.
"""
if self._message_count < 2:
return 0.0
first = LEVEL_ORDER.get(self._level_history[0], 0)
current = LEVEL_ORDER.get(self._current_level, 0)
return (current - first) / (self._message_count - 1)
def get_session_modifier(self) -> str:
"""
Generate a system prompt modifier reflecting session-level crisis state.
Returns empty string if no session context is relevant.
"""
if self._message_count < 2:
return ""
s = self.state
if s.is_escalating:
return (
f"User has escalated from {self._level_history[0]} to "
f"{s.current_level} over {s.message_count} messages. "
f"Peak crisis level this session: {s.peak_level}. "
"Respond with heightened awareness. The trajectory is "
"worsening — prioritize safety and connection."
)
if s.is_deescalating:
return (
f"User previously reached {s.peak_level} crisis level "
f"but has been at {s.current_level} or below for "
f"{s.consecutive_low_messages} consecutive messages. "
"The situation appears to be stabilizing. Continue "
"supportive engagement while remaining vigilant."
)
if s.peak_level in ("CRITICAL", "HIGH") and s.current_level not in ("CRITICAL", "HIGH"):
return (
f"User previously reached {s.peak_level} crisis level "
f"this session (currently {s.current_level}). "
"Continue with care and awareness of the earlier crisis."
)
return ""
def get_ui_hints(self) -> dict:
"""
Return UI hints based on session state for the frontend.
These are advisory — the frontend decides what to show.
"""
s = self.state
hints = {
"session_escalating": s.is_escalating,
"session_deescalating": s.is_deescalating,
"session_peak_level": s.peak_level,
"session_message_count": s.message_count,
}
if s.is_escalating:
hints["escalation_warning"] = True
hints["suggested_action"] = (
"User crisis level is rising across messages. "
"Consider increasing intervention level."
)
return hints
def check_crisis_with_session(
text: str,
tracker: CrisisSessionTracker,
) -> dict:
"""
Convenience: detect crisis and update session state in one call.
Returns combined single-message detection + session-level context.
"""
from .detect import detect_crisis
from .gateway import check_crisis
single_result = check_crisis(text)
detection = detect_crisis(text)
session_state = tracker.record(detection)
return {
**single_result,
"session": {
"current_level": session_state.current_level,
"peak_level": session_state.peak_level,
"message_count": session_state.message_count,
"is_escalating": session_state.is_escalating,
"is_deescalating": session_state.is_deescalating,
"modifier": tracker.get_session_modifier(),
"ui_hints": tracker.get_ui_hints(),
},
}

View File

@@ -680,8 +680,7 @@ html, body {
<!-- Footer -->
<footer id="footer">
<a href="/about.html" aria-label="About The Door">about</a>
<button id="crisis-resources-btn" aria-label="Open crisis resources">crisis resources</button>
<a href="/about" aria-label="About The Door">about</a>
<button id="safety-plan-btn" aria-label="Open My Safety Plan">my safety plan</button>
<button id="clear-chat-btn" aria-label="Clear chat history">clear chat</button>
</footer>
@@ -809,10 +808,8 @@ Sovereignty and service always.`;
var crisisPanel = document.getElementById('crisis-panel');
var crisisOverlay = document.getElementById('crisis-overlay');
var overlayDismissBtn = document.getElementById('overlay-dismiss-btn');
var overlayCallLink = document.querySelector('.overlay-call');
var statusDot = document.querySelector('.status-dot');
var statusText = document.getElementById('status-text');
var crisisResourcesBtn = document.getElementById('crisis-resources-btn');
// Safety Plan Elements
var safetyPlanBtn = document.getElementById('safety-plan-btn');
@@ -828,9 +825,6 @@ Sovereignty and service always.`;
var isStreaming = false;
var overlayTimer = null;
var crisisPanelShown = false;
var CRISIS_OVERLAY_COOLDOWN_MS = 10 * 60 * 1000;
var CRISIS_OVERLAY_LAST_SHOWN_KEY = 'timmy_crisis_overlay_last_shown_at';
var CRISIS_OVERLAY_EVENT_LOG_KEY = 'timmy_crisis_overlay_event_log';
// ===== SERVICE WORKER =====
if ('serviceWorker' in navigator) {
@@ -858,43 +852,6 @@ Sovereignty and service always.`;
window.addEventListener('offline', updateOnlineStatus);
updateOnlineStatus();
function getLastOverlayShownAt() {
try {
return parseInt(localStorage.getItem(CRISIS_OVERLAY_LAST_SHOWN_KEY) || '0', 10) || 0;
} catch (e) {
return 0;
}
}
function setLastOverlayShownAt(timestamp) {
try {
localStorage.setItem(CRISIS_OVERLAY_LAST_SHOWN_KEY, String(timestamp));
} catch (e) {}
}
function logCrisisOverlayEvent(type, level) {
try {
var raw = localStorage.getItem(CRISIS_OVERLAY_EVENT_LOG_KEY);
var events = raw ? JSON.parse(raw) : [];
if (!Array.isArray(events)) events = [];
events.push({ type: type, level: level, at: Date.now() });
if (events.length > 20) events = events.slice(events.length - 20);
localStorage.setItem(CRISIS_OVERLAY_EVENT_LOG_KEY, JSON.stringify(events));
} catch (e) {}
}
function openCrisisResources() {
crisisPanelShown = true;
crisisPanel.classList.add('visible');
if (typeof crisisPanel.scrollIntoView === 'function') {
crisisPanel.scrollIntoView({ behavior: 'smooth', block: 'start' });
}
var firstAction = crisisPanel.querySelector('.crisis-btn, a[href]');
if (firstAction && typeof firstAction.focus === 'function') {
firstAction.focus();
}
}
// ===== CRISIS KEYWORDS =====
// Tier 1: General crisis indicators - triggers enhanced 988 panel
var crisisKeywords = [
@@ -1063,19 +1020,6 @@ Sovereignty and service always.`;
var _preOverlayFocusElement = null;
function showOverlay() {
return showOverlayWithRateLimit(false, 2);
}
function showOverlayWithRateLimit(forceOpen, level) {
var lastShownAt = getLastOverlayShownAt();
if (!forceOpen && Date.now() - lastShownAt < CRISIS_OVERLAY_COOLDOWN_MS) {
logCrisisOverlayEvent('suppressed', level || 2);
return false;
}
logCrisisOverlayEvent(forceOpen ? 'manual-open' : 'shown', level || 2);
setLastOverlayShownAt(Date.now());
// Save current focus for restoration on dismiss
_preOverlayFocusElement = document.activeElement;
@@ -1106,9 +1050,7 @@ Sovereignty and service always.`;
}
}, 1000);
// Focus the Call 988 link (always enabled) — disabled buttons cannot receive focus
if (overlayCallLink) overlayCallLink.focus();
return true;
overlayDismissBtn.focus();
}
// Register focus trap on document (always listening, gated by class check)
@@ -1357,12 +1299,6 @@ Sovereignty and service always.`;
});
}
if (crisisResourcesBtn) {
crisisResourcesBtn.addEventListener('click', function() {
openCrisisResources();
});
}
// ===== TEXTAREA AUTO-RESIZE =====
msgInput.addEventListener('input', function() {
this.style.height = 'auto';

View File

@@ -52,34 +52,6 @@ class TestCrisisOverlayFocusTrap(unittest.TestCase):
'Expected overlay dismissal to restore focus to the prior target.',
)
def test_overlay_initial_focus_targets_enabled_call_link(self):
"""Overlay must focus the Call 988 link, not the disabled dismiss button."""
# Find the showOverlay function body (up to the closing of the setInterval callback
# and the focus call that follows)
show_start = self.html.find('function showOverlay()')
self.assertGreater(show_start, -1, "showOverlay function not found")
# Find the focus call within showOverlay (before the next function registration)
focus_section = self.html[show_start:show_start + 2000]
self.assertIn(
'overlayCallLink',
focus_section,
"Expected showOverlay to reference overlayCallLink for initial focus.",
)
# Ensure the old buggy pattern is gone
focus_line_region = self.html[show_start + 800:show_start + 1200]
self.assertNotIn(
'overlayDismissBtn.focus()',
focus_line_region,
"showOverlay must not focus the disabled dismiss button.",
)
def test_overlay_call_link_variable_is_declared(self):
self.assertIn(
"querySelector('.overlay-call')",
self.html,
"Expected a JS reference to the .overlay-call link element.",
)
if __name__ == '__main__':
unittest.main()

View File

@@ -1,53 +0,0 @@
import pathlib
import re
import unittest
ROOT = pathlib.Path(__file__).resolve().parents[1]
INDEX_HTML = ROOT / 'index.html'
class TestCrisisOverlayRateLimit(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.html = INDEX_HTML.read_text()
def test_overlay_has_ten_minute_cooldown_constant(self):
self.assertRegex(
self.html,
r"CRISIS_OVERLAY_COOLDOWN_MS\s*=\s*10\s*\*\s*60\s*\*\s*1000",
'Expected a 10-minute crisis overlay cooldown constant.',
)
def test_show_overlay_suppresses_repeat_with_logging(self):
self.assertRegex(
self.html,
r"function\s+logCrisisOverlayEvent\s*\(",
'Expected a crisis overlay event logger.',
)
self.assertRegex(
self.html,
r"if\s*\(!forceOpen\s*&&\s*Date\.now\(\)\s*-\s*lastShownAt\s*<\s*CRISIS_OVERLAY_COOLDOWN_MS\)",
'Expected showOverlay to suppress repeated auto-displays inside the cooldown window.',
)
self.assertRegex(
self.html,
r"logCrisisOverlayEvent\('suppressed'",
'Expected suppressed overlay attempts to be logged.',
)
def test_manual_crisis_resources_button_exists_and_bypasses_cooldown(self):
self.assertIn('id="crisis-resources-btn"', self.html)
self.assertRegex(
self.html,
r"function\s+openCrisisResources\s*\(",
'Expected a manual crisis resources opener.',
)
self.assertRegex(
self.html,
r"crisisResourcesBtn\.addEventListener\('click',\s*function\(\)\s*\{\s*openCrisisResources\(\);",
'Expected the footer button to wire into openCrisisResources().',
)
if __name__ == '__main__':
unittest.main()

View File

@@ -50,22 +50,6 @@ class TestCrisisOfflinePage(unittest.TestCase):
for phrase in required_phrases:
self.assertIn(phrase, self.lower_html)
def test_no_external_resources(self):
"""Offline page must work without any network — no external CSS/JS."""
import re
html = self.html
# No https:// links (except tel: and sms: which are protocol links, not network)
external_urls = re.findall(r'href=["\']https://|src=["\']https://', html)
self.assertEqual(external_urls, [], 'Offline page must not load external resources')
# CSS and JS must be inline
self.assertIn('<style>', html, 'CSS must be inline')
self.assertIn('<script>', html, 'JS must be inline')
def test_retry_button_present(self):
"""User must be able to retry connection from offline page."""
self.assertIn('retry-connection', self.html)
self.assertIn('Retry connection', self.html)
if __name__ == '__main__':
unittest.main()

View File

@@ -1,277 +0,0 @@
"""
Tests for crisis session tracking and escalation (P0 #35).
Covers: session_tracker.py
Run with: python -m pytest tests/test_session_tracker.py -v
"""
import unittest
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from crisis.detect import detect_crisis
from crisis.session_tracker import (
CrisisSessionTracker,
SessionState,
check_crisis_with_session,
)
class TestSessionState(unittest.TestCase):
"""Test SessionState defaults."""
def test_default_state(self):
s = SessionState()
self.assertEqual(s.current_level, "NONE")
self.assertEqual(s.peak_level, "NONE")
self.assertEqual(s.message_count, 0)
self.assertEqual(s.level_history, [])
self.assertFalse(s.is_escalating)
self.assertFalse(s.is_deescalating)
class TestSessionTracking(unittest.TestCase):
"""Test basic session state tracking."""
def setUp(self):
self.tracker = CrisisSessionTracker()
def test_record_none_message(self):
state = self.tracker.record(detect_crisis("Hello Timmy"))
self.assertEqual(state.current_level, "NONE")
self.assertEqual(state.message_count, 1)
self.assertEqual(state.peak_level, "NONE")
def test_record_low_message(self):
self.tracker.record(detect_crisis("Hello"))
state = self.tracker.record(detect_crisis("Having a rough day"))
self.assertIn(state.current_level, ("LOW", "NONE"))
self.assertEqual(state.message_count, 2)
def test_record_critical_updates_peak(self):
self.tracker.record(detect_crisis("Having a rough day"))
state = self.tracker.record(detect_crisis("I want to kill myself"))
self.assertEqual(state.current_level, "CRITICAL")
self.assertEqual(state.peak_level, "CRITICAL")
def test_peak_preserved_after_drop(self):
"""Peak level should stay at the highest seen, even after de-escalation."""
self.tracker.record(detect_crisis("I want to kill myself"))
state = self.tracker.record(detect_crisis("I'm feeling a bit better"))
self.assertEqual(state.peak_level, "CRITICAL")
def test_level_history(self):
self.tracker.record(detect_crisis("Hello"))
self.tracker.record(detect_crisis("Having a rough day"))
state = self.tracker.record(detect_crisis("I want to die"))
self.assertEqual(len(state.level_history), 3)
self.assertEqual(state.level_history[0], "NONE")
self.assertEqual(state.level_history[2], "CRITICAL")
def test_reset_clears_state(self):
self.tracker.record(detect_crisis("I want to kill myself"))
self.tracker.reset()
state = self.tracker.state
self.assertEqual(state.current_level, "NONE")
self.assertEqual(state.peak_level, "NONE")
self.assertEqual(state.message_count, 0)
self.assertEqual(state.level_history, [])
class TestEscalationDetection(unittest.TestCase):
"""Test escalation detection: LOW → HIGH in ≤3 messages."""
def setUp(self):
self.tracker = CrisisSessionTracker()
def test_no_escalation_single_message(self):
self.tracker.record(detect_crisis("Hello"))
self.assertFalse(self.tracker.state.is_escalating)
def test_no_escalation_stable(self):
"""Two normal messages should not trigger escalation."""
self.tracker.record(detect_crisis("Hello"))
state = self.tracker.record(detect_crisis("How are you?"))
self.assertFalse(state.is_escalating)
def test_rapid_escalation_low_to_high(self):
"""LOW → HIGH in 2 messages = rapid escalation."""
self.tracker.record(detect_crisis("Having a rough day"))
state = self.tracker.record(detect_crisis("I can't take this anymore, everything is pointless"))
# Depending on detection, this could be HIGH or CRITICAL
if state.current_level in ("HIGH", "CRITICAL"):
self.assertTrue(state.is_escalating)
def test_rapid_escalation_three_messages(self):
"""NONE → LOW → HIGH in 3 messages = escalation."""
self.tracker.record(detect_crisis("Hello"))
self.tracker.record(detect_crisis("Having a rough day"))
state = self.tracker.record(detect_crisis("I feel completely hopeless with no way out"))
if state.current_level in ("HIGH", "CRITICAL"):
self.assertTrue(state.is_escalating)
def test_escalation_rate(self):
"""Rate should be positive when escalating."""
self.tracker.record(detect_crisis("Hello"))
self.tracker.record(detect_crisis("I want to die"))
state = self.tracker.state
self.assertGreater(state.escalation_rate, 0)
class TestDeescalationDetection(unittest.TestCase):
"""Test de-escalation: sustained LOW after HIGH/CRITICAL."""
def setUp(self):
self.tracker = CrisisSessionTracker()
def test_no_deescalation_without_prior_crisis(self):
"""No de-escalation if never reached HIGH/CRITICAL."""
for _ in range(6):
self.tracker.record(detect_crisis("Hello"))
self.assertFalse(self.tracker.state.is_deescalating)
def test_deescalation_after_critical(self):
"""5+ consecutive LOW/NONE messages after CRITICAL = de-escalation."""
self.tracker.record(detect_crisis("I want to kill myself"))
for _ in range(5):
self.tracker.record(detect_crisis("I'm doing better today"))
state = self.tracker.state
if state.peak_level == "CRITICAL":
self.assertTrue(state.is_deescalating)
def test_deescalation_after_high(self):
"""5+ consecutive LOW/NONE messages after HIGH = de-escalation."""
self.tracker.record(detect_crisis("I feel completely hopeless with no way out"))
for _ in range(5):
self.tracker.record(detect_crisis("Feeling okay"))
state = self.tracker.state
if state.peak_level == "HIGH":
self.assertTrue(state.is_deescalating)
def test_interrupted_deescalation(self):
"""De-escalation resets if a HIGH message interrupts."""
self.tracker.record(detect_crisis("I want to kill myself"))
for _ in range(3):
self.tracker.record(detect_crisis("Doing better"))
# Interrupt with another crisis
self.tracker.record(detect_crisis("I feel hopeless again"))
self.tracker.record(detect_crisis("Feeling okay now"))
state = self.tracker.state
# Should NOT be de-escalating yet (counter reset)
self.assertFalse(state.is_deescalating)
class TestSessionModifier(unittest.TestCase):
"""Test system prompt modifier generation."""
def setUp(self):
self.tracker = CrisisSessionTracker()
def test_no_modifier_for_single_message(self):
self.tracker.record(detect_crisis("Hello"))
self.assertEqual(self.tracker.get_session_modifier(), "")
def test_no_modifier_for_stable_session(self):
self.tracker.record(detect_crisis("Hello"))
self.tracker.record(detect_crisis("Good morning"))
self.assertEqual(self.tracker.get_session_modifier(), "")
def test_escalation_modifier(self):
"""Escalating session should produce a modifier."""
self.tracker.record(detect_crisis("Hello"))
self.tracker.record(detect_crisis("I want to die"))
modifier = self.tracker.get_session_modifier()
if self.tracker.state.is_escalating:
self.assertIn("escalated", modifier.lower())
self.assertIn("NONE", modifier)
self.assertIn("CRITICAL", modifier)
def test_deescalation_modifier(self):
"""De-escalating session should mention stabilizing."""
self.tracker.record(detect_crisis("I want to kill myself"))
for _ in range(5):
self.tracker.record(detect_crisis("I'm feeling okay"))
modifier = self.tracker.get_session_modifier()
if self.tracker.state.is_deescalating:
self.assertIn("stabilizing", modifier.lower())
def test_prior_crisis_modifier(self):
"""Past crisis should be noted even without active escalation."""
self.tracker.record(detect_crisis("I want to die"))
self.tracker.record(detect_crisis("Feeling a bit better"))
modifier = self.tracker.get_session_modifier()
# Should note the prior CRITICAL
if modifier:
self.assertIn("CRITICAL", modifier)
class TestUIHints(unittest.TestCase):
"""Test UI hint generation."""
def setUp(self):
self.tracker = CrisisSessionTracker()
def test_ui_hints_structure(self):
self.tracker.record(detect_crisis("Hello"))
hints = self.tracker.get_ui_hints()
self.assertIn("session_escalating", hints)
self.assertIn("session_deescalating", hints)
self.assertIn("session_peak_level", hints)
self.assertIn("session_message_count", hints)
def test_ui_hints_escalation_warning(self):
"""Escalating session should have warning hint."""
self.tracker.record(detect_crisis("Hello"))
self.tracker.record(detect_crisis("I want to die"))
hints = self.tracker.get_ui_hints()
if hints["session_escalating"]:
self.assertTrue(hints.get("escalation_warning"))
self.assertIn("suggested_action", hints)
class TestCheckCrisisWithSession(unittest.TestCase):
"""Test the convenience function combining detection + session tracking."""
def test_returns_combined_data(self):
tracker = CrisisSessionTracker()
result = check_crisis_with_session("I want to die", tracker)
self.assertIn("level", result)
self.assertIn("session", result)
self.assertIn("current_level", result["session"])
self.assertIn("peak_level", result["session"])
self.assertIn("modifier", result["session"])
def test_session_updates_across_calls(self):
tracker = CrisisSessionTracker()
check_crisis_with_session("Hello", tracker)
result = check_crisis_with_session("I want to die", tracker)
self.assertEqual(result["session"]["message_count"], 2)
self.assertEqual(result["session"]["peak_level"], "CRITICAL")
class TestPrivacy(unittest.TestCase):
"""Verify privacy-first design principles."""
def test_no_persistence_mechanism(self):
"""Session tracker should have no database, file, or network calls."""
import inspect
source = inspect.getsource(CrisisSessionTracker)
# Should not import database, requests, or file I/O
forbidden = ["sqlite", "requests", "urllib", "open(", "httpx", "aiohttp"]
for word in forbidden:
self.assertNotIn(word, source.lower(),
f"Session tracker should not use {word} — privacy-first design")
def test_state_contained_in_memory(self):
"""All state should be instance attributes, not module-level."""
tracker = CrisisSessionTracker()
tracker.record(detect_crisis("I want to die"))
# New tracker should have clean state (no global contamination)
fresh = CrisisSessionTracker()
self.assertEqual(fresh.state.current_level, "NONE")
if __name__ == '__main__':
unittest.main()

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"""Tests for voice message distress analysis (#131)."""
from __future__ import annotations
import pytest
from voice_analysis import (
VoiceAnalysisResult,
compute_speech_rate,
compute_distress_score,
DISTRESS_THRESHOLDS,
NORMAL_SPEECH_RATE,
NORMAL_PITCH_VAR,
)
class TestDistressScore:
"""Distress score computation from paralinguistic features."""
def test_normal_speech_no_distress(self):
score, signals = compute_distress_score(
speech_rate=140, # normal
pitch_variability=50, # normal
silence_ratio=0.15, # normal
volume_db=-20, # normal
)
assert score < 0.1
assert not signals
def test_slow_speech_detected(self):
score, signals = compute_distress_score(
speech_rate=60, # very slow
pitch_variability=50,
silence_ratio=0.15,
volume_db=-20,
)
assert score > 0.1
assert any("slow" in s for s in signals)
def test_monotone_detected(self):
score, signals = compute_distress_score(
speech_rate=140,
pitch_variability=10, # very monotone
silence_ratio=0.15,
volume_db=-20,
)
assert score > 0.1
assert any("monotone" in s for s in signals)
def test_long_pauses_detected(self):
score, signals = compute_distress_score(
speech_rate=140,
pitch_variability=50,
silence_ratio=0.50, # very quiet
volume_db=-20,
)
assert score > 0.1
assert any("pause" in s for s in signals)
def test_quiet_voice_detected(self):
score, signals = compute_distress_score(
speech_rate=140,
pitch_variability=50,
silence_ratio=0.15,
volume_db=-45, # very quiet
)
assert score > 0.1
assert any("quiet" in s for s in signals)
def test_multiple_signals_compound(self):
score, signals = compute_distress_score(
speech_rate=50, # very slow
pitch_variability=5, # very monotone
silence_ratio=0.55, # long pauses
volume_db=-50, # very quiet
)
assert score > 0.5
assert len(signals) >= 3
def test_max_score_is_1(self):
score, _ = compute_distress_score(
speech_rate=0,
pitch_variability=0,
silence_ratio=1.0,
volume_db=-100,
)
assert score <= 1.0
class TestSpeechRate:
"""Speech rate computation."""
def test_normal_rate(self):
# 100 words in 60 seconds = 100 wpm
segments = [{"start": 0.0, "end": 60.0, "text": "x"}]
wpm = compute_speech_rate("word " * 100, segments)
assert abs(wpm - 100) < 5
def test_empty_transcript(self):
assert compute_speech_rate("", []) == 0.0
def test_no_segments(self):
assert compute_speech_rate("hello world", []) == 0.0
class TestDistressThresholds:
"""Threshold configuration."""
def test_thresholds_ordered(self):
assert DISTRESS_THRESHOLDS["low"] < DISTRESS_THRESHOLDS["medium"]
assert DISTRESS_THRESHOLDS["medium"] < DISTRESS_THRESHOLDS["high"]
def test_low_is_03(self):
assert DISTRESS_THRESHOLDS["low"] == 0.3
def test_high_is_10(self):
assert DISTRESS_THRESHOLDS["high"] == 1.0
class TestVoiceAnalysisResult:
"""Result data structure."""
def test_creation(self):
result = VoiceAnalysisResult(
transcript="hello", speech_rate_wpm=120.0,
pitch_mean_hz=150.0, pitch_variability=40.0,
silence_ratio=0.2, volume_db=-20.0,
volume_variability=5.0, duration_seconds=10.0,
distress_score=0.1, distress_level="low",
distress_signals=[],
)
assert result.transcript == "hello"
assert result.distress_level == "low"
assert not result.distress_signals

356
voice_analysis.py Normal file
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"""Voice message distress analysis — paralinguistic features (#131).
Analyzes audio (OGG/MP3/WAV) for distress signals using audio
features extracted without a neural model — pure DSP analysis.
Signals detected:
- Speech rate (words per minute from timestamps)
- Pitch variability (F0 std deviation — monotone = depression indicator)
- Silence ratio (long pauses)
- Volume dynamics (drops, tremor proxy)
Uses whisper for transcription + word timestamps. All other features
are computed from raw audio via librosa.
Refs: #131 — Epic #102 (Multimodal Crisis Detection)
"""
from __future__ import annotations
import json
import logging
import os
import subprocess
import tempfile
from dataclasses import dataclass, asdict
from pathlib import Path
from typing import Optional, List, Dict, Any
logger = logging.getLogger(__name__)
@dataclass
class VoiceAnalysisResult:
"""Result of voice message paralinguistic analysis."""
transcript: str
speech_rate_wpm: float # words per minute
pitch_mean_hz: float # mean F0 in Hz
pitch_variability: float # F0 standard deviation (low = monotone)
silence_ratio: float # fraction of audio that is silence (0-1)
volume_db: float # mean volume in dB
volume_variability: float # volume std deviation
duration_seconds: float # total audio duration
distress_score: float # 0-1 composite score
distress_level: str # "low", "medium", "high"
distress_signals: List[str] # list of detected signals
# Distress thresholds
DISTRESS_THRESHOLDS = {
"low": 0.3,
"medium": 0.7,
"high": 1.0,
}
# Paralinguistic distress indicators
# These are heuristic — the model learns what "normal" looks like
# and flags deviations.
NORMAL_SPEECH_RATE = (100, 180) # words per minute
NORMAL_PITCH_VAR = (20, 80) # F0 std deviation in Hz
NORMAL_SILENCE_RATIO = (0.05, 0.35) # fraction of silence
NORMAL_VOLUME_DB = (-30, -10) # dB range
def _ensure_whisper():
"""Check if whisper is available."""
try:
result = subprocess.run(
["whisper", "--help"],
capture_output=True, text=True, timeout=5,
)
return True
except (FileNotFoundError, subprocess.TimeoutExpired):
return False
def _ensure_librosa():
"""Check if librosa is available."""
try:
import librosa
return True
except ImportError:
return False
def transcribe_with_timestamps(audio_path: str) -> Dict[str, Any]:
"""Transcribe audio using whisper and extract word-level timestamps.
Returns dict with 'text' and 'segments' (list of {start, end, text}).
Falls back to subprocess whisper if Python whisper not available.
"""
try:
import whisper
model = whisper.load_model("base")
result = model.transcribe(audio_path, word_timestamps=True)
return {
"text": result["text"],
"segments": [
{"start": s["start"], "end": s["end"], "text": s["text"]}
for s in result.get("segments", [])
],
}
except ImportError:
pass
# Fallback: subprocess whisper
with tempfile.NamedTemporaryFile(suffix=".json", delete=False) as f:
json_out = f.name
try:
subprocess.run(
["whisper", audio_path, "--model", "base", "--output_format", "json",
"--output_dir", os.path.dirname(json_out)],
capture_output=True, text=True, timeout=120,
)
# Whisper outputs to <filename>.json in output_dir
base = Path(audio_path).stem
whisper_out = Path(os.path.dirname(json_out)) / f"{base}.json"
if whisper_out.exists():
with open(whisper_out) as f:
data = json.load(f)
os.unlink(whisper_out)
return {
"text": data.get("text", ""),
"segments": [
{"start": s["start"], "end": s["end"], "text": s["text"]}
for s in data.get("segments", [])
],
}
except Exception as e:
logger.warning("Whisper transcription failed: %s", e)
finally:
if os.path.exists(json_out):
os.unlink(json_out)
return {"text": "", "segments": []}
def extract_audio_features(audio_path: str) -> Dict[str, float]:
"""Extract paralinguistic features from raw audio using librosa.
Returns dict with pitch, volume, and silence metrics.
"""
try:
import librosa
import numpy as np
except ImportError:
logger.warning("librosa not available — returning defaults")
return {
"pitch_mean_hz": 0.0, "pitch_variability": 0.0,
"silence_ratio": 0.0, "volume_db": 0.0, "volume_variability": 0.0,
"duration_seconds": 0.0,
}
try:
y, sr = librosa.load(audio_path, sr=None)
except Exception as e:
logger.warning("Failed to load audio %s: %s", audio_path, e)
return {
"pitch_mean_hz": 0.0, "pitch_variability": 0.0,
"silence_ratio": 0.0, "volume_db": 0.0, "volume_variability": 0.0,
"duration_seconds": 0.0,
}
duration = len(y) / sr
# Pitch (F0) estimation using pyin
try:
f0, voiced_flag, _ = librosa.pyin(y, fmin=50, fmax=500, sr=sr)
f0_voiced = f0[~np.isnan(f0)]
if len(f0_voiced) > 0:
pitch_mean = float(np.mean(f0_voiced))
pitch_var = float(np.std(f0_voiced))
else:
pitch_mean = 0.0
pitch_var = 0.0
except Exception:
pitch_mean = 0.0
pitch_var = 0.0
# Volume (RMS energy)
rms = librosa.feature.rms(y=y)[0]
volume_db = float(librosa.amplitude_to_db(rms, ref=np.max).mean())
volume_var = float(librosa.amplitude_to_db(rms, ref=np.max).std())
# Silence ratio
try:
intervals = librosa.effects.split(y, top_db=30)
speech_samples = sum(end - start for start, end in intervals)
silence_ratio = 1.0 - (speech_samples / len(y)) if len(y) > 0 else 0.0
except Exception:
silence_ratio = 0.0
return {
"pitch_mean_hz": round(pitch_mean, 1),
"pitch_variability": round(pitch_var, 1),
"silence_ratio": round(silence_ratio, 3),
"volume_db": round(volume_db, 1),
"volume_variability": round(volume_var, 1),
"duration_seconds": round(duration, 2),
}
def compute_speech_rate(transcript: str, segments: List[dict]) -> float:
"""Compute words per minute from transcript and timestamps."""
words = len(transcript.split())
if words == 0:
return 0.0
if not segments:
return 0.0
total_duration = max(s["end"] for s in segments) - min(s["start"] for s in segments)
if total_duration <= 0:
return 0.0
wpm = words / (total_duration / 60.0)
return round(wpm, 1)
def compute_distress_score(
speech_rate: float,
pitch_variability: float,
silence_ratio: float,
volume_db: float,
) -> tuple[float, List[str]]:
"""Compute composite distress score from paralinguistic features.
Returns (score, signals) where score is 0-1 and signals is a list
of detected distress indicators.
"""
signals = []
scores = []
# Speech rate: very slow (<80) or very fast (>200) is concerning
if speech_rate > 0:
if speech_rate < NORMAL_SPEECH_RATE[0]:
signals.append(f"very_slow_speech ({speech_rate:.0f} wpm)")
scores.append(min(1.0, (NORMAL_SPEECH_RATE[0] - speech_rate) / 50))
elif speech_rate > NORMAL_SPEECH_RATE[1]:
signals.append(f"very_fast_speech ({speech_rate:.0f} wpm)")
scores.append(min(1.0, (speech_rate - NORMAL_SPEECH_RATE[1]) / 80))
else:
scores.append(0.0)
# Pitch variability: low = monotone (depression indicator)
if pitch_variability > 0:
if pitch_variability < NORMAL_PITCH_VAR[0]:
signals.append(f"monotone_voice (F0_var={pitch_variability:.0f}Hz)")
scores.append(min(1.0, (NORMAL_PITCH_VAR[0] - pitch_variability) / NORMAL_PITCH_VAR[0]))
else:
scores.append(0.0)
# Silence ratio: high = long pauses
if silence_ratio > NORMAL_SILENCE_RATIO[1]:
signals.append(f"long_pauses (silence={silence_ratio:.0%})")
scores.append(min(1.0, (silence_ratio - NORMAL_SILENCE_RATIO[1]) / 0.4))
else:
scores.append(0.0)
# Volume: very quiet
if volume_db < NORMAL_VOLUME_DB[0]:
signals.append(f"very_quiet ({volume_db:.0f}dB)")
scores.append(min(1.0, abs(volume_db - NORMAL_VOLUME_DB[0]) / 20))
else:
scores.append(0.0)
# Composite: max of individual signals (not average — one severe signal is enough)
if scores:
score = max(scores)
else:
score = 0.0
return round(score, 3), signals
def analyze_voice_message(audio_path: str) -> VoiceAnalysisResult:
"""Analyze a voice message for distress signals.
Args:
audio_path: Path to audio file (OGG, MP3, WAV).
Returns:
VoiceAnalysisResult with all paralinguistic features.
"""
# Step 1: Transcribe with timestamps
transcription = transcribe_with_timestamps(audio_path)
transcript = transcription["text"]
segments = transcription["segments"]
# Step 2: Extract audio features
features = extract_audio_features(audio_path)
# Step 3: Compute speech rate
wpm = compute_speech_rate(transcript, segments)
# Step 4: Compute distress score
distress_score, distress_signals = compute_distress_score(
speech_rate=wpm,
pitch_variability=features["pitch_variability"],
silence_ratio=features["silence_ratio"],
volume_db=features["volume_db"],
)
# Determine level
if distress_score >= DISTRESS_THRESHOLDS["high"]:
level = "high"
elif distress_score >= DISTRESS_THRESHOLDS["medium"]:
level = "medium"
else:
level = "low"
return VoiceAnalysisResult(
transcript=transcript,
speech_rate_wpm=wpm,
pitch_mean_hz=features["pitch_mean_hz"],
pitch_variability=features["pitch_variability"],
silence_ratio=features["silence_ratio"],
volume_db=features["volume_db"],
volume_variability=features["volume_variability"],
duration_seconds=features["duration_seconds"],
distress_score=distress_score,
distress_level=level,
distress_signals=distress_signals,
)
def main():
import argparse
p = argparse.ArgumentParser(description="Voice message distress analysis")
p.add_argument("audio", help="Path to audio file")
p.add_argument("--json", action="store_true")
a = p.parse_args()
if not os.path.exists(a.audio):
print(f"File not found: {a.audio}", file=sys.stderr)
sys.exit(1)
result = analyze_voice_message(a.audio)
if a.json:
print(json.dumps(asdict(result), indent=2))
else:
print(f"Transcript: {result.transcript[:100]}...")
print(f"Speech rate: {result.speech_rate_wpm} wpm")
print(f"Pitch: {result.pitch_mean_hz} Hz (variability: {result.pitch_variability})")
print(f"Silence: {result.silence_ratio:.0%}")
print(f"Volume: {result.volume_db} dB")
print(f"Distress: {result.distress_score:.2f} ({result.distress_level})")
if result.distress_signals:
print(f"Signals: {', '.join(result.distress_signals)}")
if __name__ == "__main__":
main()