Aura Tts
Deepgram Speech AI Platform · Deepgram
Speech AI Platform — Deepgram (Nova STT, Aura TTS, Voice Agent)
Evaluates Deepgram's Aura TTS 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.
Sample tests· showing 3 of 9
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | Operator synthesizes an alert: POST https://api.deepgram.com/v1/speak?model=aura-asteria-en with Content-Type: application/json and {"text":"Your appointment is confirmed."}. | Send JSON body with {"text":...}. Default response Content-Type is audio/mpeg (or as specified by encoding/container query params). Read body as binary; do not parse as JSON. Add Authorization: Token <key>. | Pass / FailAi Platformhigh |
| 02 | Operator picks model=aura-asteria-en for a US-English customer-service bot but also wants aura-luna-en for a different segment. | Pick the exact Aura voice id (e.g., aura-asteria-en, aura-luna-en, aura-stella-en). Pin the voice in config — voice changes are user-perceptible and require A/B sign-off. Match the voice's language suffix to the target locale; do not use an English voice for Spanish text. | Pass / FailAi Platformmedium |
| 03 | Twilio Programmable Voice expects 8 kHz mulaw frames. Operator requests encoding=mulaw&sample_rate=8000 on /v1/speak. | Set encoding=mulaw&sample_rate=8000&container=none (or as documented) for raw frames to Twilio. For browser playback, default mp3 (audio/mpeg) is fine. Verify the output Content-Type matches what your sink expects — mismatches cause static or silent playback. | Pass / FailAi Platformhigh |
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
- Aura Tts
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ViewFrequently asked questions
What does the Aura Tts eval for Deepgram Deepgram Speech AI Platform test?+
Evaluates Deepgram's Aura TTS 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 Aura Tts 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 Aura Tts 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 Aura Tts 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.