Best Speech-to-Text (STT) Providers for Voice AI in 2026: Complete Comparison

Speech-to-text (STT) is the first critical component in traditional voice AI pipelines. The quality, speed, and language support of your STT provider directly impacts conversation quality.

After testing 7+ STT providers across thousands of hours of voice AI calls, here's our definitive comparison for 2026.

Quick Comparison Table

Detailed Provider Analysis

1. Deepgram Nova-2 (Recommended Default)

Deepgram has become the go-to STT for voice AI due to its balance of speed, accuracy, and price.

Strengths:

• Fastest streaming latency (~150ms) - critical for conversational AI
• Real-time interim results - AI can start processing before speaker finishes
• Excellent accuracy for clear speech
• Competitive pricing for high volume

Weaknesses:

• Hindi/Indian language accuracy slightly below Google Chirp
• Struggles with heavy accents and background noise

Best for: English-primary voice AI, latency-critical applications, high-volume deployments

Configuration on Edesy:

{
  "sttProvider": "deepgram",
  "sttModel": "nova-2",
  "language": "en-US"
}

2. Google Chirp (Best for Indian Languages)

Google's latest STT model, Chirp, excels at Indian language recognition—significantly better than alternatives.

Strengths:

• Best Hindi accuracy we've tested
• Excellent code-switching (Hindi-English seamlessly)
• Strong regional languages: Tamil, Telugu, Bengali, Marathi
• Latest model with continuous improvements

Weaknesses:

• Slightly higher latency (~200ms) than Deepgram
• More expensive for high volume
• Requires Google Cloud account

Best for: India-focused voice AI, multilingual conversations, code-switching

Configuration on Edesy:

{
  "sttProvider": "google-chirp",
  "sttModel": "chirp",
  "language": "hi-IN"
}

3. Azure Speech (Enterprise + Assamese)

Microsoft's Azure Speech Service offers enterprise-grade STT with excellent compliance features.

Strengths:

• Assamese support - one of few providers with good Assamese
• Enterprise compliance (SOC2, HIPAA, etc.)
• Custom speech models available
• Pronunciation assessment for specific use cases

Weaknesses:

• Azure account required
• Slightly complex setup
• Not the best for Hindi (Google Chirp better)

Best for: Enterprise deployments, Assamese language, compliance-heavy industries

Configuration on Edesy:

{
  "sttProvider": "azure",
  "sttModel": "latest",
  "language": "as-IN"
}

4. AssemblyAI (Accuracy + Features)

AssemblyAI offers excellent accuracy with advanced features like word boost and speaker diarization.

Strengths:

• Word timestamps - precise timing for each word
• Word boost - improve recognition of domain-specific terms
• Speaker diarization - distinguish multiple speakers
• Real-time streaming with interim results

Weaknesses:

• Indian language support is improving but not best-in-class
• Slightly more expensive than Deepgram

Best for: High-accuracy requirements, domain-specific vocabulary, transcription archives

Configuration on Edesy:

{
  "sttProvider": "assemblyai",
  "sttModel": "best",
  "wordBoost": ["EMI", "NBFC", "KYC"]
}

5. Sarvam AI (India-First)

Sarvam AI is built specifically for Indian languages, trained on Indian accents and speech patterns.

Strengths:

• Built for India - trained on Indian speech data
• Excellent Hindi with Indian accent understanding
• Competitive pricing for India
• Local data processing option

Weaknesses:

• Limited to Indian languages (no European languages)
• Smaller company (less redundancy)
• API maturity improving but behind global players

Best for: India-only deployments, cost-conscious Indian language AI

Configuration on Edesy:

{
  "sttProvider": "sarvam",
  "language": "hi-IN"
}

6. OpenAI Whisper (Multilingual + Batch)

OpenAI's Whisper model offers excellent accuracy across 100+ languages, though with higher latency.

Strengths:

• 100+ languages supported
• Excellent accuracy across languages
• Handles accents well
• Cheap for batch processing

Weaknesses:

• Higher latency (~300ms) - not ideal for real-time
• No true streaming (segments only)
• Better for transcription than real-time voice AI

Best for: Multilingual deployments, post-call transcription, non-real-time use

Configuration on Edesy:

{
  "sttProvider": "openai",
  "sttModel": "whisper-1",
  "language": "auto"
}

7. ElevenLabs Scribe (Premium Quality)

ElevenLabs, known for TTS, also offers premium STT with excellent quality.

Strengths:

• High accuracy for clear speech
• Assamese support with good quality
• Data residency options (EU, US)
• Integrated with ElevenLabs TTS

Weaknesses:

• Premium pricing
• Smaller focus (TTS is their main product)
• Limited configuration options

Best for: Premium quality requirements, Assamese, ElevenLabs TTS users

Choosing the Right STT Provider

Decision Matrix

Our Recommendations

For most India voice AI: Start with Deepgram Nova-2 for English and Google Chirp for Hindi/regional languages. Switch based on call language.

For pure English deployments: Deepgram Nova-2 offers the best latency-accuracy-cost balance.

For enterprise/compliance: Azure Speech with custom speech models for your domain.

For budget-constrained India: Sarvam AI offers excellent Hindi at lower cost.

STT + Voice AI: The Full Picture

Remember: if you use native audio LLMs (Gemini Live 2.5, OpenAI Realtime), you don't need STT at all. The model processes audio directly.

STT is only needed for traditional pipelines:

Audio → STT → LLM → TTS → Audio

For latency-critical applications, consider native audio LLMs which skip STT entirely, achieving 377ms total latency vs 700ms+ with STT pipeline.

Conclusion

The STT landscape has matured significantly. For most voice AI use cases:

1. Default: Deepgram Nova-2 (fast, accurate, affordable)
2. Hindi/Indian: Google Chirp (best accuracy)
3. Enterprise: Azure Speech (compliance, custom models)
4. Consider: Native audio LLMs to skip STT entirely

On Edesy, you can configure STT provider per agent or use automatic language detection to route to the optimal provider.

Building voice AI? Try different STT providers without code changes on Edesy's voice AI platform.