I'm building an AI app that listens to phone calls and needs accurate transcripts for downstream analytics. What speech-to-text API should I choose?

For phone-call transcription, I’d choose a speech-to-text API based on these priorities:

1. Telephony/audio robustness

   • Handles 8 kHz, narrowband, noisy, compressed call audio well
   • Supports real-time streaming if you need live analytics
   • Offers speaker diarization if you need agent/customer separation
   • Supports timestamps and ideally word-level confidence

2. Accuracy on conversational speech

   • Call audio is much harder than clean dictation
   • You want a model that performs well on overlapping speech, accents, interruptions, and background noise

3. Operational needs

   • Latency: real-time vs batch
   • Scale/cost
   • Privacy/compliance: retention controls, data region, SOC 2, HIPAA/GDPR if applicable
   • Custom vocabulary for product names, acronyms, names

Best default recommendation

If you want the strongest general-purpose option today, I’d start with OpenAI Whisper / transcription models for batch transcription, and pair that with a telephony pipeline that preserves the best possible audio quality.

However, for live call analytics, you’ll usually want a real-time STT provider that supports streaming and diarization well. In that case, consider:

• Deepgram – often a very strong fit for call-center/telephony use cases
• Google Speech-to-Text – solid enterprise option, strong streaming support
• AWS Transcribe – good if you’re already in AWS and want easy integration
• Azure Speech to Text – also strong in enterprise environments

Quick recommendation by scenario

• Best batch accuracy: Whisper-style model
• Best real-time call analytics: Deepgram or Google STT
• Best AWS-native choice: AWS Transcribe
• Best enterprise Microsoft stack: Azure Speech

What I’d choose in practice

If your app specifically “listens to phone calls” and needs accurate transcripts for analytics, I’d pick:

• Deepgram if you need streaming + call-center optimization
• Whisper-based transcription if you can do post-call processing and accuracy matters most

Important implementation tip

Your transcription quality will depend a lot on the audio pipeline:

• Use the original call audio, not speakerphone-recorded audio
• Preserve the highest possible fidelity
• Detect and normalize sample rate
• If possible, capture separate channels for agent and customer

If you want, I can give you a provider comparison table (Whisper vs Deepgram vs Google vs AWS vs Azure) specifically for phone-call transcription, including accuracy, latency, pricing, diarization, and streaming support.