Deepgram
For DeepgramAI PlatformTranscription Accuracy

Batch Stt Rest

Deepgram Speech AI Platform · Deepgram

Speech AI Platform — Deepgram (Nova STT, Aura TTS, Voice Agent)

Evaluates Deepgram's Batch STT (REST) across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Speech AI Platform eval coverage.

About Deepgram

Deepgram is a speech-AI platform offering streaming and batch speech-to-text (Nova), Aura text-to-speech, speaker diarization, redaction, and smart formatting across 30+ languages — used by voice-agent platforms, contact centers, and media teams.

Employees

~150

Industry

Speech AI

Headquarters

San Francisco, CA

Sample tests· showing 3 of 9

#InputExpected behaviorCheck
01

Operator submits POST https://api.deepgram.com/v1/listen?model=nova-3 with Content-Type: application/json and body {"url":"https://media.example.com/call.wav"}.

Use JSON body with {"url":...} for URL ingestion. Deepgram fetches the media server-side; the URL must be publicly fetchable (or signed). Verify the media server returns audio/* Content-Type and a reasonable Content-Length. Treat non-2xx fetch errors as a Deepgram 400 with details in body.

Pass / FailAi Platformhigh
02

Operator transcribes a 45-minute clinical interview and picks model=nova-3-medical.

Pick model=nova-3-medical for medical-domain audio (clinical vocabulary boost); pin the version. For general business audio use nova-3-general. Do not switch model per retry; benchmark on a held-out fixture before changing the default model in production.

Pass / FailAi Platformmedium
03

Operator uploads raw audio bytes directly: POST /v1/listen with Content-Type: audio/wav and binary body.

Set Content-Type to the actual media (audio/wav, audio/mpeg, audio/mp4, etc.) and put bytes in the body. Do not also include a url body — direct upload and URL fetch are mutually exclusive. For unrecognized container, fall back to encoding/sample_rate query params with audio/* MIME.

Pass / FailAi Platformhigh

Unlock full benchmark

6 more test cases

Use this benchmark

How this eval is graded

Grade against expected.ideal_behavior and expected.rubric. Per-criterion pass requires mean >= 4.0 and no criterion below 3.

Rubric criteria

  • Deepgram
  • Ai Platform
  • Batch Stt Rest

Recommended for

Deepgram Speech AI PlatformDeepgram customers

Works with

Related evals

Frequently asked questions

What does the Batch Stt Rest eval for Deepgram Deepgram Speech AI Platform test?+

Evaluates Deepgram's Batch STT (REST) across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Speech AI Platform eval coverage.

How is the Batch Stt Rest eval scored?+

The judge rubric: Grade against expected.ideal_behavior and expected.rubric. Per-criterion pass requires mean >= 4.0 and no criterion below 3.

How many test cases does this eval pack include?+

The Batch Stt Rest pack for Deepgram Deepgram Speech AI Platform contains 9 test cases. 3 sample cases are shown free on this page; the full set runs in a Corsac workspace.

How do I run this eval?+

Sign up for Corsac, connect your model or agent endpoint, and run the Batch Stt Rest pack as-is or after customizing thresholds. Results land in your workspace with per-case scores, and you can gate releases on the pack in CI via the REST API.

Run this eval in your workspace

Connect your data, configure thresholds, and review results with your team.