Voice AI Language Coverage Checker
Explore language support across 30+ languages. See which STT, LLM, and TTS providers work best for each language and their quality levels.
Languages
Excellent STT
Excellent TTS
Total Voices
Quality Levels Explained
Excellent
Native-quality, production-ready
Good
Reliable with minor limitations
Limited
Basic support, test before production
Why Multilingual Voice AI Matters
Expand your reach and improve customer experience with native-language support
Reach More Customers
Only 17% of the world speaks English as a first language. Multilingual voice AI expands your addressable market dramatically.
Better Customer Experience
Customers prefer to interact in their native language. Native-language support increases satisfaction by 70%.
Higher Conversion Rates
Sales calls in the customer's native language convert 2-3x better than English-only approaches in non-English markets.
Reduced Staffing Complexity
Instead of hiring multilingual agents, let voice AI handle multiple languages with consistent quality.
Understanding the Components
What each voice AI component does and how to evaluate quality
Speech-to-Text (STT)
Accuracy of transcribing spoken language. Excellent means near-native accuracy; Good means occasional errors with accents or fast speech.
Key Consideration:
Consider dialect variations (e.g., Latin American vs. Spain Spanish) and background noise handling.
Language Model (LLM)
Quality of AI understanding and response generation. Excellent means fluent, culturally-aware responses; Good means functional but may miss nuances.
Key Consideration:
Major languages have excellent LLM support. Test cultural appropriateness and idiom handling for your specific use case.
Text-to-Speech (TTS)
Natural-sounding voice synthesis. Excellent means indistinguishable from human; Good means clearly synthetic but pleasant.
Key Consideration:
Number of voice options varies by language. Consider gender, age, and accent variety for your brand.
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Frequently Asked Questions
How do I choose the best provider for my language?
Start with the recommended providers shown in the language details. For production use, test multiple options with native speakers. Quality can vary by dialect and use case. Consider: STT accuracy with your typical audio quality, LLM cultural appropriateness, and TTS naturalness for your brand voice.
Can voice AI handle code-switching (mixing languages)?
Some combinations work well (e.g., English + Hindi is common in India). STT providers like Deepgram and Whisper handle code-switching reasonably well. For best results, configure your voice AI to expect code-switching and test with real-world audio samples.
What about regional accents and dialects?
Major languages often have dialect-specific models (e.g., US English vs. UK English, Brazilian Portuguese vs. European Portuguese). Check provider documentation for specific dialect support. Generally, models trained on diverse data handle accents better.
How accurate are the quality ratings?
Quality ratings are based on provider benchmarks, real-world testing, and user feedback. 'Excellent' typically means Word Error Rate under 5% for STT and CMOS scores above 4.0 for TTS. Actual quality depends on your specific use case, audio quality, and vocabulary.
Can I use different providers for different languages?
Yes! Many voice AI platforms (including Edesy) support per-language or per-agent provider configuration. This lets you optimize for quality and cost in each market. For example, use Deepgram for English but Azure for Hindi.
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Build Multilingual Voice AI
Edesy Voice AI supports 24+ languages out of the box with the best providers for each. Start building global voice experiences today.