ConvoZen Speech-to-Text
Built for 8 kHz Customer Calls. Not Studio Podcasts.
Generic hyperscaler STT models are typically trained on pristine audiobooks, causing them to fail when a customer calls from a noisy environment—like a train station—using a low-quality headset.
ConvoZen's STT is purpose-built for the chaotic reality of B2C Voice AI in India. Trained on over 50,000 hours of real telephonic customer conversations.
Trusted by customer-obsessed teams at
What Sets Us Apart
Designed for Indian Conversational Speech
Performance That Moves Metrics
8–12% WER Across Languages.
Stop accepting 15–20% Word Error Rates as the cost of doing business. By training our models directly on call-center-style speech, we achieve dramatically lower WER. For our clients, this translates directly to fewer reprompts, higher containment rates, and more accurate downstream NLU.
- ✓Hindi: 18.5% → 8.2% WER
- ✓English: 17.2% → 9.1% WER
- ✓Tamil: 20.1% → 11.3% WER
- ✓Telugu: 19.0% → 10.5% WER
WER Comparison
Hyperscalers vs. ConvoZen — Lower is better
| Language | Hyperscaler WER | ConvoZen WER | Improvement |
|---|---|---|---|
| Hindi | 18.5% | 8.2% | ↓ 56% |
| English | 17.2% | 9.1% | ↓ 47% |
| Tamil | 20.1% | 11.3% | ↓ 44% |
| Telugu | 19% | 10.5% | ↓ 45% |
Telephony-Native Advantage
Optimized for Short, Rapid Turns.
Most modern, attention-based models require long conversational context to perform well. However, Voice AI demands fast, accurate recognition of short, rapid turns (e.g., "Yes", "Kal subah", "1234"). We have optimized our architecture specifically for the short-utterance context typical of real-world IVR and voicebot flows.
- ✓Optimized for 8 kHz, 24 kbps short utterances
- ✓50,000+ hours of real telephonic training data
- ✓5,000+ hours of careful human annotation
- ✓Purpose-built for IVR and voicebot flows
Ship in Days
Developer-Friendly Integration.
Deploying ConvoZen is fast and developer-friendly, equipped with everything an engineering team needs to go live.
- ✓Streaming + batch transcription
- ✓Word-level timestamps & confidence scoring
- ✓Custom vocabulary and phrase boosts
- ✓PII masking & redaction (Aadhaar, PAN, Credit Cards)
- ✓Cloud / VPC / On-prem deployment
Integration & Core Capabilities
Everything You Need, Out of the Box
9 Supported Languages
Native coverage for English, Hindi, Tamil, Telugu, Kannada, Marathi, Bengali, Gujarati, and Malayalam.
Real-Time Streaming & Batch
Achieve <150ms latency via WebSocket for live voicebots, alongside REST endpoints for bulk post-call analytics.
Granular Output
Receive word-level timestamps, accurate speaker diarization, and precise confidence scoring.
Enterprise Context
Boost accuracy with custom vocabularies and automatically redact PII (Aadhaar, PAN, Credit Cards) on the fly.
Flexible Deployment
Available via Managed Cloud, Private VPC, or On-Premises.
Proven Reliability
Vetted in production for over 4 years powering the NoBroker consumer voice journey.
Use Cases