Multi-language updates

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Quick reference

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Understanding multilingual agents

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How multilingual agents work

• Detect the caller’s language automatically
• Switch languages mid-conversation if the caller changes
• Maintain language-specific knowledge for each language
• Use appropriate voices per language
• Handle mixed-language queries (code-switching)

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Supported languages

• English (en)
• Spanish (es)
• French (fr)
• German (de)
• Italian (it)
• Portuguese (pt)
• Dutch (nl)
• Polish (pl)
• Russian (ru)
• Japanese (ja)
• Korean (ko)
• Chinese Mandarin (zh)
• Arabic (ar)
• Hindi (hi)
• And many more

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Adding or removing languages

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Adding a new language

1. Go to Channels > Voice > Agent Voice
2. Click Change to open the Voice Library
3. Use the Language filter to find voices in your target language
4. Select and apply a voice for the new language
5. Add language-specific knowledge (see below)
6. Update Agent Behaviour rules to handle the new language
7. Test in Agent Chat
8. Publish when ready

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Removing a language

1. Go to Channels > Voice > Agent Voice
2. Remove the voice associated with the language you want to drop
3. Update any language-specific knowledge and functions
4. Publish the change

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Managing language-specific knowledge

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Managed Topics with language variants

1. Go to Build > Knowledge > Managed Topics tab
2. Create or edit a topic
3. Add language variants for each supported language
4. Provide translations or culturally-appropriate content
5. Save and test

• Question: “What are your hours?”
• Answer: “We’re open Monday through Friday, 9 AM to 5 PM.”

• Question: “¿Cuál es su horario?”
• Answer: “Estamos abiertos de lunes a viernes, de 9 AM a 5 PM.”

• Question: “Quelles sont vos heures d’ouverture?”
• Answer: “Nous sommes ouverts du lundi au vendredi, de 9h à 17h.”

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Connected knowledge per language

• URL sources - Add separate URLs for each language version of your website
• File sources - Upload language-specific PDFs or documents
• Integration sources - Configure APIs to return language-specific data

• English: https://example.com/en/faq
• Spanish: https://example.com/es/preguntas-frecuentes
• French: https://example.com/fr/faq

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When to use shared vs. language-specific knowledge

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Updating voices for each language

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Selecting language-appropriate voices

1. Go to Channels > Voice > Agent Voice
2. Click Change to open the Voice Library
3. Filter by Language and Region to find native voices for each language
4. Preview each voice with custom text in the target language
5. Select and apply

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Voice quality considerations

• Use native voices - Don’t use an English voice for Spanish
• Match regional accents - Use Mexican Spanish for Mexico, Castilian for Spain
• Test pronunciation - Ensure the voice handles language-specific characters
• Consider gender and tone - Match your brand across languages

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Multilingual voice models

from polyai.voice import ElevenLabsVoice

conv.set_voice(
    ElevenLabsVoice(
        provider_voice_id="multilingual_voice_id",
        model_id="eleven_multilingual_v2"  # Supports 30+ languages
    )
)

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Handling language detection

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Automatic language detection

1. The caller speaks
2. ASR (Automatic Speech Recognition) identifies the language
3. The agent responds in the detected language

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Tuning detection behavior

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Explicit language selection

1. Create a Managed Topic for language selection
2. Add options like “Press 1 for English, 2 for Spanish”
3. Use a function to set the language:

def set_language(language_code):
    conv.set_language(language_code)
    return {"utterance": f"Switching to {language_code}."}

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Handling code-switching

• Example: “I need to hacer una reservación for mañana.”

• Use multilingual voice models that support multiple languages
• Test with realistic mixed-language scenarios
• Consider your target audience’s code-switching patterns
• Adjust Agent Behaviour rules to accommodate mixed-language input

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Fixing translation issues

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Common translation problems

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Updating translations

1. Identify the problematic response in Conversation Review
2. Find the corresponding Managed Topic or function
3. Edit the language-specific variant
4. Test in Agent Chat with native speakers
5. Publish when satisfied

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Using professional translators

• Export knowledge - Download Managed Topics as CSV
• Send to translators - Provide context and domain glossary
• Import translations - Upload the translated CSV
• Review and test - Verify quality before publishing

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Language-specific functions

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Adding language parameters to functions

def get_store_hours(location, language="en"):
    # Fetch hours from API
    hours = api.get_hours(location)
    
    # Format response based on language
    if language == "es":
        return {"utterance": f"Estamos abiertos de {hours['open']} a {hours['close']}."}
    elif language == "fr":
        return {"utterance": f"Nous sommes ouverts de {hours['open']} à {hours['close']}."}
    else:
        return {"utterance": f"We're open from {hours['open']} to {hours['close']}."}

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Accessing the current language

def dynamic_response():
    current_language = conv.language
    conv.log.info(f"Caller language: {current_language}")
    
    # Use language-specific logic
    if current_language == "es":
        return {"utterance": "Respuesta en español"}
    else:
        return {"utterance": "Response in English"}

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Language-specific API calls

def search_products(query):
    language = conv.language
    
    # Call API with language parameter
    results = requests.get(
        "https://api.example.com/search",
        params={"q": query, "lang": language}
    )
    
    return {"utterance": format_results(results, language)}

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Testing multilingual agents

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Test in Agent Chat

1. Open Agent Chat
2. Select a language from the dropdown
3. Speak or type in that language
4. Verify the agent responds correctly
5. Try switching languages mid-conversation

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Test language detection

1. Start a conversation in one language
2. Switch to another language mid-call
3. Verify the agent detects and switches
4. Check for false positives (switching when it shouldn’t)

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Test with native speakers

• Recruit testers - Find native speakers of each language
• Provide scenarios - Give realistic test cases
• Gather feedback - Ask about naturalness, accuracy, and cultural appropriateness
• Iterate - Refine based on feedback

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Common test scenarios

• Language switching - Start in English, switch to Spanish
• Mixed queries - Ask questions with code-switching
• Accents and dialects - Test regional variations
• Background noise - Verify ASR works in noisy environments
• Edge cases - Test with uncommon words or phrases

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Troubleshooting multilingual issues

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Common issues and solutions

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Debugging language issues

1. Check Conversation Review - See which language was detected
2. Review Diagnosis logs - Look for language-related errors
3. Test in Agent Chat - Reproduce the issue
4. Verify settings - Ensure language is properly configured
5. Check knowledge coverage - Confirm content exists for that language

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Best practices

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Content management

• Maintain parity - Ensure all languages have equivalent content
• Localize, don’t just translate - Adapt for cultural context
• Use consistent terminology - Create a glossary for domain terms
• Update all languages together - Don’t let translations lag behind

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Voice and audio

• Use native voices - Never use a non-native voice for a language
• Match regional preferences - Consider accent and dialect
• Test pronunciation - Verify proper handling of special characters
• Adjust speech rate - Some languages sound better at different speeds

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Testing and quality

• Test with native speakers - Don’t rely on non-native testers
• Monitor language distribution - Track which languages are used most
• Review low-confidence calls - Identify language detection issues
• A/B test translations - Try different phrasings to find what works best

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Maintenance routine

• Monthly language audit - Review content parity across languages
• Quarterly voice review - Ensure voices still sound natural
• Regular translation updates - Keep content current in all languages
• Monitor language-specific metrics - Track performance per language

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Common workflows

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Adding a new language to an existing agent

1. Add a voice for the language from the Voice Library at Channels > Voice > Agent Voice
2. Update Agent Behaviour rules to handle the new language
3. Export existing Managed Topics
4. Translate content (use professional translators)
5. Import translated content
6. Add language-specific Connected knowledge sources
7. Update functions to handle the new language
8. Test thoroughly with native speakers
9. Publish to Sandbox
10. Run Test Sets for the new language
11. Promote to Pre-release for UAT
12. Promote to Live

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Updating translations across all languages

1. Identify the content to update (e.g., new business hours)
2. Update the default language version
3. Export Managed Topics
4. Send to translators with context
5. Import translated updates
6. Test each language in Agent Chat
7. Publish and promote

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Fixing a language detection issue

1. Review calls where language switching was incorrect
2. Check Diagnosis logs for language detection events
3. Adjust language-switching behavior in Agent Behaviour rules
4. Test with the problematic scenario
5. If needed, add explicit language selection option
6. Publish and monitor

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Optimizing for a specific language

1. Review analytics for that language
2. Identify common queries and issues
3. Add language-specific knowledge
4. Adjust voice settings (rate, pitch)
5. Test with native speakers
6. Iterate based on feedback

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Related pages

• Multi-language setup - Configure language support
• Voice Library - Browse and select voices per language
• Managed Topics - Add language variants
• Connected knowledge - Language-specific sources
• Functions - Handle language in code