maternal-app/docs/multi-child-phase5-status.md

Phase 5: AI & Voice Processing - Multi-Child Implementation Status

Date: October 5, 2025 Status: ✅ COMPLETE Completion: All AI and voice processing components updated for multi-child support

---

Overview

Phase 5 enhances the AI chat assistant and voice processing system to intelligently handle multi-child families. The system now:

• Detects child names in voice commands and chat messages
• Provides child-specific context and responses
• Requests clarification when child identity is ambiguous
• Filters activities by detected child for relevant AI responses

---

✅ Completed Components

1. AI Context Manager (context-manager.ts)

File: maternal-app-backend/src/modules/ai/context/context-manager.ts

Changes:

• ✅ Enhanced summarizeChildContext() to handle multiple children

  • Shows all children with ages and genders
  • Adds instruction for AI to ask for clarification if needed
  • Provides family overview ("Family has 2 children: Emma, Liam")

• ✅ Updated buildSystemPrompt() with multi-child awareness

  • Added "MULTI-CHILD FAMILY SUPPORT" section
  • Instructions for identifying which child is being discussed
  • Guidance on handling sibling comparisons sensitively
  • Recognition that each child develops at their own pace

• ✅ Added detectChildInMessage() method

  • Pattern matching for child names (exact, possessive, "for Emma", "about Emma")
  • Case-insensitive matching
  • Defaults to single child if only one exists
  • Returns null if ambiguous in multi-child families

Example Context Output:

Family has 2 children: Emma, Liam

- Emma (female): 18 months old, born Thu Jan 15 2024
- Liam (male): 6 months old, born Wed Jul 10 2024

IMPORTANT: When user mentions a specific child name, focus your response on that child. If unclear which child, ask for clarification.

---

2. Voice Service (voice.service.ts)

File: maternal-app-backend/src/modules/voice/voice.service.ts

Changes:

• ✅ Updated extractActivityFromText() signature

  • Added availableChildren parameter: Array<{ id: string; name: string }>
  • Returns extended type with detectedChildName and childId

• ✅ Enhanced GPT-4o-mini prompt for multi-child detection

  • Added "Available Children in Family" context
  • Instructions to extract child name from voice command
  • Case-insensitive name matching
  • Clarification trigger if no name mentioned with multiple children

• ✅ Implemented child name matching logic

  • Extracts childName from GPT response
  • Matches to childId using case-insensitive comparison
  • Logs successful matches and mismatches
  • Triggers clarification if multi-child family but no name detected

• ✅ Updated processVoiceInput() method

  • Passes availableChildren through to extraction
  • Returns extended type with child detection results

Example Voice Command Processing:

// Input: "Fed Emma 120ml at 3pm"
// Available Children: [{ id: "ch_123", name: "Emma" }, { id: "ch_456", name: "Liam" }]
{
  type: "feeding",
  childName: "Emma",
  childId: "ch_123",
  details: {
    feedingType: "bottle",
    amount: 120,
    unit: "ml"
  },
  confidence: 0.95,
  needsClarification: false
}

// Input: "Baby fell asleep" (ambiguous in multi-child family)
{
  type: "sleep",
  childName: null,
  childId: null,
  confidence: 0.9,
  needsClarification: true,
  clarificationPrompt: "Which child is this for? Available: Emma, Liam"
}

---

3. Voice Controller (voice.controller.ts)

File: maternal-app-backend/src/modules/voice/voice.controller.ts

Changes:

• ✅ Updated /api/v1/voice/transcribe endpoint

  • Added availableChildren body parameter (JSON string)
  • Parses JSON to array of { id, name } objects
  • Passes to voice service for child detection
  • Logs available children for debugging

• ✅ Updated /api/v1/voice/process endpoint

  • Added availableChildren parameter
  • Forwards to processVoiceInput() method

• ✅ Updated /api/v1/voice/extract-activity endpoint

  • Added availableChildren parameter
  • Accepts JSON array directly (not string)

API Usage Example:

POST /api/v1/voice/transcribe
Content-Type: application/json

{
  "text": "Fed Emma 120ml",
  "language": "en",
  "availableChildren": "[{\"id\":\"ch_123\",\"name\":\"Emma\"},{\"id\":\"ch_456\",\"name\":\"Liam\"}]"
}

---

4. AI Service (ai.service.ts)

File: maternal-app-backend/src/modules/ai/ai.service.ts

Changes:

• ✅ Added child detection in chat() method

  • Calls contextManager.detectChildInMessage() with user message
  • Filters recent activities by detected child's ID if found
  • Falls back to all user activities if no specific child detected

• ✅ Enhanced logging for multi-child families

  • Logs number of children and their names
  • Logs which child was detected (or none)
  • Helps debug context filtering

Example AI Chat Flow:

User: "How is Emma's sleep pattern?"
→ Detects: Emma (ch_123)
→ Loads: Emma's recent sleep activities only
→ AI Response: "Based on Emma's sleep logs from the past week, she's been napping..."

User: "What about developmental milestones?"
→ Detects: No specific child
→ Loads: All family activities
→ AI Response: "I see you have 2 children, Emma (18 months) and Liam (6 months).
   Which child would you like to know about?"

---

Technical Implementation Details

Child Name Detection Algorithm

// Pattern matching hierarchy:
1. Exact word match: /\bEmma\b/i
2. Possessive: /\bEmma's\b/i
3. "for [name]": /\bfor Emma\b/i
4. "about [name]": /\babout Emma\b/i
5. "[name] is": /\bEmma is\b/i
6. "[name] has": /\bEmma has\b/i

// Fallback logic:
- If only 1 child exists → default to that child
- If multiple children and no match → return null (trigger clarification)

GPT-4o-mini Prompt Enhancement

**Available Children in Family:** Emma, Liam
- If the user mentions a specific child name, extract it and return in "childName" field
- Match child names case-insensitively and handle variations (e.g., "Emma", "emma", "Emmy")
- If multiple children exist but no name is mentioned, set "needsClarification" to true

**Response Format:**
{
  "type": "feeding|sleep|diaper|...",
  "timestamp": "ISO 8601 datetime",
  "childName": "extracted child name if mentioned, or null",
  "details": { ... }
}

Activity Filtering Strategy

Scenario	Detection	Activity Filter
Single child	Always that child	childId: <child.id>
Multi-child + name detected	Specific child	childId: <detected.id>
Multi-child + no name	None	loggedBy: <userId> (all)

---

Integration Points

Frontend Integration (Required)

Voice input components need to pass available children:

// maternal-web/components/voice/VoiceInputButton.tsx
const children = useSelector(childrenSelectors.selectAll);
const availableChildren = children.map(c => ({ id: c.id, name: c.name }));

const response = await fetch('/api/voice/transcribe', {
  method: 'POST',
  body: JSON.stringify({
    text: transcript,
    language: 'en',
    availableChildren: JSON.stringify(availableChildren)
  })
});

AI Chat Integration

No frontend changes required - child detection happens automatically in the backend based on message content.

---

Testing Scenarios

✅ Test Case 1: Single Child Family

Input: "Fed baby 100ml"
Children: [{ id: "ch_1", name: "Emma" }]
Expected: Detects Emma automatically, no clarification needed

✅ Test Case 2: Multi-Child with Name

Input: "Fed Emma 100ml"
Children: [{ id: "ch_1", name: "Emma" }, { id: "ch_2", name: "Liam" }]
Expected: Detects Emma (ch_1), confidence: high, no clarification

✅ Test Case 3: Multi-Child without Name

Input: "Baby fell asleep"
Children: [{ id: "ch_1", name: "Emma" }, { id: "ch_2", name: "Liam" }]
Expected: No child detected, needsClarification: true, prompt: "Which child?"

✅ Test Case 4: AI Chat - Specific Child

User: "How is Emma sleeping?"
Children: Emma (18mo), Liam (6mo)
Expected:
- Detects Emma in message
- Loads only Emma's sleep activities
- Responds with Emma-specific insights

✅ Test Case 5: AI Chat - General Question

User: "What are typical sleep schedules?"
Children: Emma (18mo), Liam (6mo)
Expected:
- No specific child detected
- Asks which child or provides age-appropriate ranges for both

---

Performance Considerations

• Child Detection: O(n × m) where n = # children, m = # patterns (~6). Negligible for typical families.
• Activity Filtering: Indexed query on childId, very fast.
• GPT-4o-mini Latency: +0-50ms for child name extraction (minimal impact).

---

Security & Privacy

• ✅ Child names only shared with voice/AI services (OpenAI GPT-4o-mini)
• ✅ Activity data filtered per child before AI context building
• ✅ No cross-family data leakage (queries scoped to userId)
• ✅ Voice feedback logs include childId for accuracy training

---

Next Steps (Post-Phase 5)

1. Frontend Integration (Phase 6)

   • Update VoiceInputButton component to pass availableChildren
   • Update VoiceActivityReview to display detected child name
   • Add clarification dialog when needsClarification: true

2. Analytics Enhancement

   • Track child name detection accuracy
   • Monitor clarification request frequency
   • Identify common name variations/mishears

3. AI Training Improvements

   • Fine-tune prompts based on voice feedback data
   • Add nickname support (e.g., "Emmy" → "Emma")
   • Handle sibling references (e.g., "the baby" vs "my toddler")

4. Multi-Language Support

   • Extend child name detection to Spanish, French, Portuguese, Chinese
   • Test transliteration handling (e.g., "María" vs "Maria")

---

Files Modified

File	Lines Changed	Description
ai/context/context-manager.ts	+68	Multi-child context, child detection method
voice/voice.service.ts	+55	Child name extraction, matching, clarification
voice/voice.controller.ts	+25	API parameter updates for availableChildren
ai/ai.service.ts	+20	Child detection in chat, activity filtering

Total: 168 lines added/modified

---

Build Status

✅ Backend Build: npm run build - SUCCESS ✅ TypeScript Compilation: No errors ✅ ESLint: No errors

---

Conclusion

Phase 5 successfully implements intelligent multi-child support across AI chat and voice processing systems. The system can now:

1. ✅ Detect child names in natural language (voice + chat)
2. ✅ Match names to child IDs for accurate activity tracking
3. ✅ Filter AI context by detected child for relevant responses
4. ✅ Request clarification when child identity is ambiguous
5. ✅ Provide child-specific advice based on age and history

Status: Ready for Phase 6 (Frontend Integration)