Language coverage

Documentation Index

Fetch the complete documentation index at: https://docs.poly.ai/llms.txt

Use this file to discover all available pages before exploring further.

This page is the canonical reference for which languages PolyAI supports and which models cover them across LLM, speech recognition (ASR), and text-to-speech (TTS). For setup and runtime behavior, see Multi-language. For model selection, see Model and Raven.

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At a glance

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LLM language coverage

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Raven (recommended)

Raven is purpose-built for customer service across voice and chat. Raven 3.5 supports the following 24 languages: Arabic, Bulgarian, Cantonese, Croatian, Czech, Dutch, English, French, German, Greek, Hindi, Hindi (Romanized/Hinglish), Italian, Japanese, Korean, Mandarin (PRC), Mandarin (Taiwan), Polish, Portuguese (Brazil), Portuguese (Portugal), Serbian, Spanish (US), Swedish, Turkish. Strongest performance relative to general-purpose models: Cantonese, Italian, Korean, Mandarin (China), Mandarin (Taiwan), Spanish (US). You can keep prompts and knowledge in English and set the response language to your target language – Raven responds consistently in the target language. Quality improves further if you translate prompts and add examples in the target language.

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Third-party LLMs

When you select an OpenAI or Amazon Bedrock model on the Model page, language coverage matches that provider’s official support. Use a third-party LLM when:

• Your target language is not on the Raven list above, or
• You need a capability only the third-party model provides.

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Full list of supported response languages

PolyAI accepts the BCP 47 codes below as response languages. Pass the code in the UI or via conv.set_language().

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Models

For full model descriptions and selection guidance, see Model.

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LLM models

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ASR providers

ASR providers wired into the platform today:

• Deepgram
• Google Cloud Speech-to-Text (v1 and v2)
• NVIDIA Riva
• Amazon Transcribe
• OpenAI (Whisper)
• Fano
• NVIDIA NeMo

The platform routes requests to the best-fit provider per language and use case, with automatic fallback. See Speech recognition.

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TTS providers

TTS voice availability varies by provider and language. Browse what’s available per language in the Voice library.

• ElevenLabs
• Amazon Polly
• Azure Speech
• Cartesia
• Google Cloud Text-to-Speech
• Hume
• MiniMax
• Neuphonic
• OpenAI
• PlayHT
• Rime
• Custom TTS integrations

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Choosing a language and model

1. Pick the response language from the table above using its BCP 47 code.
2. Check Raven coverage – if your language is on the 24-language Raven list, Raven 3.5 is the recommended LLM.
3. If Raven does not cover it (for example Danish), select a third-party LLM in Voice configuration or Chat configuration. Verify the chosen model officially supports the language.
4. Confirm regional availability for Bedrock models if you are deploying outside US-1.
5. Confirm a voice exists for the language in the Voice library. Prefer native voices over multilingual fallbacks.
6. Configure ASR – defaults usually work; for domain terms see Speech recognition and ASR biasing.

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Related pages

• Multi-language – set up, test, and route multilingual agents.
• Model – compare LLM options and configure per channel.
• Raven – PolyAI’s proprietary LLM family.
• Bring your own model – connect a custom LLM endpoint.
• Speech recognition – ASR settings and biasing.
• Voice library – browse voices per language and provider.