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arXiv cs.AI· Aditya Srinivas Menon, Kumarmanas Nethil, Kavya Manohar·· 12 小时前AI 评分27

无需训练即可让冻结流式说话人日志模型追踪更多说话人:Slots Are Not Speakers 提出 Speaker Linking 方法

Slots Are Not Speakers: Training-Free Speaker Linking for Frozen Streaming Diarizers

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一种因果、免训练的链接器让冻结的流式说话人日志模型突破输出槽位上限,追踪更多说话人。它仅利用宿主模型的槽位后验与音频,在单槽活跃帧上按说话人变化切分、用现成说话人编码器嵌入并与已见说话人库匹配,只做重新标注,因此漏检与误报与宿主一致。

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Abstract:This paper presents a causal, training-free linker that allows a frozen streaming diarizer to track more speakers than it has output slots. Streaming end-to-end diarizers such as Streaming Sortformer emit a fixed number N of concurrent speaker slots. Above N speakers, they keep detecting speech but reuse slots across people, because N bounds how many speakers the model can express at once, not how many it will meet. The linker uses only the host's slot posteriors and the audio. It keeps the frames where one slot is active, splits each slot where the speaker changes, embeds each piece with an off-the-shelf speaker encoder, and matches it against a bank of speakers seen so far. It only relabels, so missed speech and false alarm are identical to the host's and every gain is a reduction in speaker confusion. On 1418 sessions from eight corpora, it reduces the 4-slot host's DER above its cap from 36.8% to 22.6%, and barely moves it below the cap. The same constants transfer to the host's 8-slot successor and to two streaming EEND hosts from a different model family. On courtroom hearings with up to 23 speakers it reduces cpWER from 82.7% to 24.4%.
Comments: Submitted to ICASSP 2027
Subjects: Sound (cs.SD); Artificial Intelligence (cs.AI)
Cite as: arXiv:2610.28053 [cs.SD]
  (or arXiv:2610.28053v1 [cs.SD] for this version)
  https://doi.org/10.48550/arXiv.2610.28053

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Aditya Srinivas Menon [view email]
[v1] Tue, 20 Oct 2026 11:40:02 UTC (78 KB)

来源:arXiv cs.AI · arxiv.org