Keysat
c7f94381e7
Recap Relay dev asked: can the diarization output include a confidence
level per segment so the UI can render "Speaker_0?" for uncertain
assignments rather than confidently mislabeling?
Answer: yes. Sortformer's diarize() with include_tensor_outputs=True
returns the per-frame per-speaker sigmoid scores (shape [B, T, 4spk],
~12.6 fps frame rate). The current code argmaxes those into segment
strings and throws the raw scores away. Now: for each output segment,
compute mean probability of the assigned speaker across the segment's
frames → confidence in [0, 1].
Implementation:
- diarizer.py: diarize_chunk() now calls diarize() with
include_tensor_outputs=True, and a new _attach_confidence() helper
derives the per-segment mean probability after parsing the segment
strings. The frame-rate is computed from tensor shape vs audio
duration (no need to hard-code the model's stride).
- All failure paths return confidence=None gracefully — Recap Relay
can treat None as "no info" or fall back to a default threshold.
Endpoint shape change: segments[] now have an optional `confidence`
field in [0, 1] (or None). All other fields unchanged. Existing callers
that ignore the field aren't affected.
Verified with a 5s test signal that the tensor has shape [1, 63, 4]
(63 frames / 5s = 12.6 fps) and values in [0, 1] (sigmoid outputs,
independent per speaker so overlap detection works). Real speech values
will be much higher than the near-zero values of the pure-tone test
signal.
Reapply patches on the Speech Models card after installing v0.13.0:2
to pick up the updated diarizer.py + main.py in the parakeet container.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
14 lines
925 B
TypeScript
14 lines
925 B
TypeScript
import { VersionInfo, IMPOSSIBLE } from '@start9labs/start-sdk'
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export const v0_1_0 = VersionInfo.of({
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version: '0.13.0:2',
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releaseNotes: {
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en_US:
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'v0.13.0:2 — per-segment confidence in diarize-chunk. Sortformer outputs per-frame per-speaker sigmoid probabilities (~12.6 fps) that we previously discarded. Now: for each diarization segment, compute mean probability of the assigned speaker across the segment\'s frames → confidence in [0, 1]. Recap Relay (and other consumers) can threshold this to render uncertain segments as "Speaker_0?" with a question mark, or to skip them entirely. Endpoint shape is otherwise unchanged — segments[].confidence is a new field, value may be None on derivation failure. Click Reapply patches on the Speech Models card after install to pick up the updated diarizer.py + main.py.',
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},
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migrations: {
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up: async ({ effects }) => {},
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down: IMPOSSIBLE,
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},
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})
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