Unverified50% confidenceFactExact time
DER does not penalize incorrect prediction of the number of speakers itself; as long as each audio segment is correctly attributed in time, the DER can still be relatively low.
1
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50%
Confidence
Long-term
Relevance
9/29/2026
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Related Claims
UnverifiedThe Diarization Error Rate (DER) is derived by summing the durations of missed detection errors, false alarm errors, and speaker confusion errors, then dividing by the total actual speech duration; a lower score is better.79% similarUnverifiedFiltering audio down to segments of a single speaker breaks pause-detection logic in a non-intuitive way, as the removal of silence segments may prevent the VAD model from correctly identifying pause boundaries.69% similarUnverified多人同时发言（鸡尾酒会问题）时AI说话人分离的准确率会显著下降68% similarUnverifiedThe latest version of pyannote.audio adopts an end-to-end neural network architecture (EEND), and the diarization error rate (DER) on standard evaluation sets has dropped below 10%.67% similar
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