{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:HXNFV7P2NG6J5ZORP3YW5JO67O","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":"a07127e46b5d20f4da002cec741a5b7567db33c097d677ecb972a2971e23b78c","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-10-31T02:11:58Z","title_canon_sha256":"92c0a70004070b03bd86e55bd94eae82957eed95dc415b9b4efc2a6cb35aba5c"},"schema_version":"1.0","source":{"id":"2210.17016","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.17016","created_at":"2026-07-05T05:12:17Z"},{"alias_kind":"arxiv_version","alias_value":"2210.17016v2","created_at":"2026-07-05T05:12:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.17016","created_at":"2026-07-05T05:12:17Z"},{"alias_kind":"pith_short_12","alias_value":"HXNFV7P2NG6J","created_at":"2026-07-05T05:12:17Z"},{"alias_kind":"pith_short_16","alias_value":"HXNFV7P2NG6J5ZOR","created_at":"2026-07-05T05:12:17Z"},{"alias_kind":"pith_short_8","alias_value":"HXNFV7P2","created_at":"2026-07-05T05:12:17Z"}],"graph_snapshots":[{"event_id":"sha256:1f7b0a0fb828cba9b630eca979a2261dc3a3c7cff9fbfa93fe0c53be45ef520e","target":"graph","created_at":"2026-07-05T05:12:17Z","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/2210.17016/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Speaker modeling is essential for many related tasks, such as speaker recognition and speaker diarization. The dominant modeling approach is fixed-dimensional vector representation, i.e., speaker embedding. This paper introduces a research and production oriented speaker embedding learning toolkit, Wespeaker. Wespeaker contains the implementation of scalable data management, state-of-the-art speaker embedding models, loss functions, and scoring back-ends, with highly competitive results achieved by structured recipes which were adopted in the winning systems in several speaker verification cha","authors_text":"Binbin Zhang, Chengdong Liang, Hongji Wang, Shuai Wang, Xu Xiang, Yanlei Deng, Yanmin Qian, Zhengyang Chen","cross_cats":["eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-10-31T02:11:58Z","title":"Wespeaker: A Research and Production oriented Speaker Embedding Learning Toolkit"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.17016","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:fa91eae931a8f621fa2807e679b8ba8926b670cf960704d79a69c279062926fc","target":"record","created_at":"2026-07-05T05:12:17Z","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":"a07127e46b5d20f4da002cec741a5b7567db33c097d677ecb972a2971e23b78c","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-10-31T02:11:58Z","title_canon_sha256":"92c0a70004070b03bd86e55bd94eae82957eed95dc415b9b4efc2a6cb35aba5c"},"schema_version":"1.0","source":{"id":"2210.17016","kind":"arxiv","version":2}},"canonical_sha256":"3dda5afdfa69bc9ee5d17ef16ea5defb802d321502167809c39d390c20640049","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3dda5afdfa69bc9ee5d17ef16ea5defb802d321502167809c39d390c20640049","first_computed_at":"2026-07-05T05:12:17.325192Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:12:17.325192Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uN+kvYmiAluI1Cjz6ikGwQ3Z8x24DAXDvcTsBzrwSzr/X9fxTAfiIPkJBL4Dm/MDmaUPIONqDqrQskTelagrDA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:12:17.325718Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.17016","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fa91eae931a8f621fa2807e679b8ba8926b670cf960704d79a69c279062926fc","sha256:1f7b0a0fb828cba9b630eca979a2261dc3a3c7cff9fbfa93fe0c53be45ef520e"],"state_sha256":"1a924446901822c7177aa0fbd604d1796612f4b39f7cfb8c9fd8732a485209ac"}