Transcription Asr And Speaker Attribution
Granola · Granola
AI meeting notes — Granola
Evaluates Granola's Transcription ASR & Speaker Attribution across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI meeting notes eval coverage.
About Granola
Granola is an AI notepad for meetings that runs locally on macOS, capturing audio from any meeting tool and generating structured, editable notes with action items and summaries — without bots or calendar integrations.
Sample tests· showing 3 of 10
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | Four engineers speak in rapid alternation on a Granola-captured Zoom call. Transcript must label at least three distinct speaker IDs or names without collapsing all speech into one block. | Speaker-attributed segments for ≥3 participants; timestamps monotonic; no single-speaker wall of text. | Pass / FailCorrectnesshigh |
| 02 | SRE standup mentions 'Kubernetes ingress', 'Postgres WAL', and 'p99 latency'. Granola transcript must preserve technical terms recognizably for downstream Granola Chat queries. | Key infra terms appear correctly or with obvious phonetic variants flagged; Granola Chat can retrieve them. | Pass / FailCorrectnesshigh |
| 03 | LatAm customer alternates Spanish pricing discussion with English product questions. Granola transcript preserves both languages in order without dropping Spanish segments. | Both languages present in transcript; no English-only filtering; diarization still attributes speaker. | Pass / FailCorrectnesshigh |
How this eval is graded
Grade against expected.ideal_behavior and expected.rubric. Penalize failure_modes.
Rubric criteria
- Granola
- Meeting Notes
- Transcription Asr And Speaker Attribution
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ViewFrequently asked questions
What does the Transcription Asr And Speaker Attribution eval for Granola Granola test?+
Evaluates Granola's Transcription ASR & Speaker Attribution across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI meeting notes eval coverage.
How is the Transcription Asr And Speaker Attribution eval scored?+
The judge rubric: Grade against expected.ideal_behavior and expected.rubric. Penalize failure_modes.
How many test cases does this eval pack include?+
The Transcription Asr And Speaker Attribution pack for Granola Granola contains 10 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 Transcription Asr And Speaker Attribution 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.
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