Diarization eval results

Source: crates/screenpipe-audio-eval/evals/ · VoxConverse dev (CC-BY-4.0) + composed workday templates + screenpipe-shaped LibriSpeech fixtures

_{DER, VAD FA, VAD FN, boundary err: lower is better. Continuity: higher is better, 1.0 = same hyp cluster across all silence gaps. Composed workday rows and screenpipe_* rows exercise screenpipe-shaped usage: meetings, background gaps, backchannels, echo leakage, and crosstalk. Raw VoxConverse rows score broadcast-quality stems for comparison. See crates/screenpipe-audio-eval/evals/README.md for methodology.}

Pipeline replay matrix

Source: generated screenpipe_* fixtures materialized into temp screenpipe SQLite DBs, then read back through search_audio. This catches storage/search regressions that pure DER scoring misses.

_{The no-secret CI matrix runs local diarization under Parakeet/Whisper engine labels across live/background and mic/system device profiles. Real Deepgram/screenpipe-cloud smoke can be run locally with --deepgram required when credentials are present.}

Transcription quality

Source: LibriSpeech test-clean (CC-BY-4.0) · per-model utterance cap · normalized lowercased word-level Levenshtein

_{WER + CER on read-aloud speech. Per-model utterance caps keep wall time bounded — tiny/parakeet at 50, the heavier large-v3-turbo-quantized at 20. See README for normalization rules.}