{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:2ZKM4T4AEYKKEI4CFEVWXX7AS2","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"99a87ba0eccad233fe1ad75cb1424f5b07d29fc8ceca7ecd06a682c522866c7d","cross_cats_sorted":["cs.AI","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-10-20T03:08:18Z","title_canon_sha256":"5236d41251543dcdcf8695595a5a16083760ae18b69210728506cd9a8452b9db"},"schema_version":"1.0","source":{"id":"2210.10985","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.10985","created_at":"2026-07-05T05:10:59Z"},{"alias_kind":"arxiv_version","alias_value":"2210.10985v2","created_at":"2026-07-05T05:10:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.10985","created_at":"2026-07-05T05:10:59Z"},{"alias_kind":"pith_short_12","alias_value":"2ZKM4T4AEYKK","created_at":"2026-07-05T05:10:59Z"},{"alias_kind":"pith_short_16","alias_value":"2ZKM4T4AEYKKEI4C","created_at":"2026-07-05T05:10:59Z"},{"alias_kind":"pith_short_8","alias_value":"2ZKM4T4A","created_at":"2026-07-05T05:10:59Z"}],"graph_snapshots":[{"event_id":"sha256:5fb8dc98b25a36492f7fb716b6d87412f2392560778a945d2c82b9b57c9932c8","target":"graph","created_at":"2026-07-05T05:10:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2210.10985/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The objective of this work is to develop a speaker recognition model to be used in diverse scenarios. We hypothesise that two components should be adequately configured to build such a model. First, adequate architecture would be required. We explore several recent state-of-the-art models, including ECAPA-TDNN and MFA-Conformer, as well as other baselines. Second, a massive amount of data would be required. We investigate several new training data configurations combining a few existing datasets. The most extensive configuration includes over 87k speakers' 10.22k hours of speech. Four evaluati","authors_text":"Bong-Jin Lee, Hee-Soo Heo, Hye-Jin Shim, Jaesong Lee, Jee-weon Jung, Joon Son Chung, Shinji Watanabe, Youngki Kwon","cross_cats":["cs.AI","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-10-20T03:08:18Z","title":"Large-scale learning of generalised representations for speaker recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.10985","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:453e142ff713d24a23e19dce03eaab746d680228e7bb4c2a5e7dd4a8636f7a70","target":"record","created_at":"2026-07-05T05:10:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"99a87ba0eccad233fe1ad75cb1424f5b07d29fc8ceca7ecd06a682c522866c7d","cross_cats_sorted":["cs.AI","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-10-20T03:08:18Z","title_canon_sha256":"5236d41251543dcdcf8695595a5a16083760ae18b69210728506cd9a8452b9db"},"schema_version":"1.0","source":{"id":"2210.10985","kind":"arxiv","version":2}},"canonical_sha256":"d654ce4f802614a22382292b6bdfe096a5d0fedb2bad7282723ebecd8f651713","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d654ce4f802614a22382292b6bdfe096a5d0fedb2bad7282723ebecd8f651713","first_computed_at":"2026-07-05T05:10:59.056742Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:10:59.056742Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G5Ag/6ua9ioeHM0D3qJhQj5jMbGxUXWpZt9TZyCI2bhnBRA9yMeEW35jRZnDG5H3nipH9E9tgcCS0rOLIJ7ZCA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:10:59.057146Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.10985","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:453e142ff713d24a23e19dce03eaab746d680228e7bb4c2a5e7dd4a8636f7a70","sha256:5fb8dc98b25a36492f7fb716b6d87412f2392560778a945d2c82b9b57c9932c8"],"state_sha256":"33b20e4ba0b1d721c853f41b44587afb9e3b4ec4799e9e029cd190c64fc33501"}