Loading...
Industry-leading speech-to-text for natural voice conversations. Choose from Deepgram, Google, Azure, or Whisper. Real-time transcription with 98%+ accuracy.
STT Providers
Latency
Accuracy
Languages
World-class STT options for every use case
Fastest and most accurate STT. Under 300ms latency, excellent noise handling. Recommended for real-time voice conversations.
Best multilingual coverage with 125+ languages. Strong support for Indian languages including Hindi, Tamil, Telugu, and more.
Enterprise-grade reliability with custom model training. Excellent for domain-specific vocabulary and accents.
High accuracy with excellent noise robustness. Great for recordings and asynchronous processing. Multilingual out of the box.
Different agents can use different STT providers. Use Deepgram for speed-critical calls, Google for regional languages.
All providers handle background noise, multiple speakers, and phone-quality audio. Clear transcription in real-world conditions.
Accurate transcription = better AI responses
<300ms Latency
Natural conversation flow
98%+ Accuracy
Industry-leading WER
Noise Robust
Works in any environment
Accent Support
Understands regional speech
Multiple Providers
No vendor lock-in
50+ Languages
Global deployment ready
Custom Vocabulary
Add domain terms
Fallback Support
Auto-switch if needed
Choose the right STT for your needs
| Provider | Speed | Accuracy | Languages | Best For |
|---|---|---|---|---|
| Deepgram Nova-2 | Ultra-Fast | Excellent | 35+ | Real-time voice calls |
| Google Cloud STT | Fast | Excellent | 125+ | Multilingual, Indian languages |
| Azure Speech | Fast | Excellent | 100+ | Enterprise, custom models |
| OpenAI Whisper | Medium | Very Good | 99 | Recordings, noise robustness |
From voice to text in milliseconds
Caller Speaks
Audio captured from call
Stream to STT
Real-time audio streaming
Transcription
Text returned in <300ms
AI Processes
LLM generates response
Real feedback on transcription quality
"Deepgram's speed is incredible. The AI responds so quickly that customers don't notice any delay. Feels like talking to a human."
<300ms Latency
Mumbai
CX Director
"Google's Hindi recognition is excellent. Our rural customers speak in mixed Hindi-English and it understands everything correctly."
98% Hindi Accuracy
Delhi
Product Head
"We tested with noisy call center audio and the transcription was still accurate. Handles real-world phone quality well."
Noise Robust
Bangalore
Tech Lead
Common questions about STT for voice AI
Deepgram Nova-2 is our recommendation for live voice calls - it offers the lowest latency (<300ms) and excellent accuracy. Google Cloud is best for multilingual scenarios, especially Indian languages. Azure is great for enterprise customization.
Audio from the phone call is streamed to the STT provider in real-time. Transcription results stream back as the caller speaks, with partial results updating until the speaker finishes. This enables natural back-and-forth conversation.
Yes, we support Hindi, Tamil, Telugu, Kannada, Malayalam, Marathi, Gujarati, Bengali, and more. Google Cloud has the broadest Indian language support, while Deepgram offers excellent Hindi recognition.
Modern STT providers are trained on diverse accents. Deepgram and Google handle Indian English accents very well. For specialized domains or heavy accents, Azure allows custom model training on your audio data.
All providers include noise suppression designed for phone-quality audio. They handle office noise, street noise, and multiple speakers. Deepgram's Nova-2 is particularly strong at isolating the primary speaker.
Yes, if you have a custom model on Azure or Google, you can configure our platform to use it. This is useful for domain-specific vocabulary (medical terms, product names, etc.) that general models might miss.
STT costs are based on audio duration processed. Deepgram and Google are competitively priced at ~$0.004-0.006 per 15 seconds. We pass through provider costs transparently as part of your usage billing.
Yes, you can configure backup STT providers. If Deepgram is slow or unavailable, automatically fall back to Google or Azure. This ensures calls continue without interruption.
Explore more AI Voice Assistant capabilities