auto segments = model.diarize_chunk(features, enc_cache, aosc_cache);
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This does not mean confusables.txt is wrong. It means confusables.txt is a visual-similarity claim that has never been empirically validated at scale. Many entries map characters to the same abstract target under NFKC decomposition (mathematical bold A to A, for instance), and the mapping is semantically correct even if the glyphs look nothing alike. But if you treat every confusables.txt entry as equally dangerous for UI security, you are generating massive false positive rates for 96.5% of the dataset.
Мощный удар Израиля по Ирану попал на видео09:41
第十六条 年满十八周岁的居民，不分民族、种族、性别、职业、家庭出身、宗教信仰、教育程度、财产状况、居住期限，都有选举权和被选举权；但是，依照法律被剥夺政治权利的人除外。