Prompt

Can you recommend a speech-to-text API for transcribing call recordings with speaker labels, timestamps, and webhooks?

Artificial Intelligence / Speech & Voice AI1 observationLast seen Oct 11, 2026

Latest observation

Oct 11, 2026OpenAI APIWeb search: off

Yes — for call recordings with speaker labels, timestamps, and webhooks, the best-fit APIs are usually:

Top recommendation: AssemblyAI

Why it fits well:

  • Speaker diarization: identifies different speakers
  • Word-level timestamps: good for syncing transcripts with audio
  • Async transcription + webhooks: ideal for call recordings
  • Easy developer experience: simple API and solid docs
  • Also offers extras like sentiment, chapters, summaries, and PII redaction

Best for: SaaS apps, call analytics, support QA, sales coaching


Strong alternatives

Deepgram

  • Very fast
  • Speaker diarization
  • Word timestamps
  • Supports async jobs and callbacks/webhooks
  • Strong for real-time and batch transcription

Best for: lower latency, high-volume pipelines, real-time or near-real-time use cases

Google Cloud Speech-to-Text

  • Reliable and scalable
  • Speaker diarization available
  • Timestamps available
  • Webhooks are not as native/simple as dedicated transcription platforms, so you often need to build orchestration yourself

Best for: teams already on GCP, especially if you want broader cloud integration

AWS Transcribe

  • Speaker identification/diarization
  • Timestamps
  • Asynchronous transcription jobs
  • Integrates well with AWS eventing patterns, though “webhooks” typically require extra setup via Lambda/SNS/SQS

Best for: AWS-native stacks

OpenAI Whisper-based solutions

  • Good accuracy, especially for noisy audio
  • But speaker labels and webhooks are not native in the same way
  • Usually requires additional tooling for diarization and job completion notifications

Best for: custom pipelines where you can assemble diarization separately


Quick recommendation by priority

  • Simplest all-in-one for call recordings: AssemblyAI
  • Best for speed/scale: Deepgram
  • Best if you’re already in a cloud ecosystem: AWS Transcribe or Google STT
  • Best raw transcription quality in difficult audio: Whisper-based stack, but more work for speaker labels/webhooks

What I’d choose

If you specifically need:

  • speaker labels
  • timestamps
  • webhooks
  • and you want the least engineering effort

I’d start with AssemblyAI.

If you want, I can also give you:

  1. a feature comparison table,
  2. a pricing/latency comparison, or
  3. a sample API workflow for uploading a call recording and receiving a webhook callback.

Observation history

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