{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:AGRB3UF7Z2BXMCBE7JKB7GEQEB","short_pith_number":"pith:AGRB3UF7","schema_version":"1.0","canonical_sha256":"01a21dd0bfce83760824fa541f989020421f4f190f4637fc991205102b8b78c2","source":{"kind":"arxiv","id":"1612.04056","version":2},"attestation_state":"computed","paper":{"title":"Joint Bayesian Gaussian discriminant analysis for speaker verification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SD","authors_text":"Haotian Xu, Yiyan Wang, Zhijian Ou","submitted_at":"2016-12-13T08:13:03Z","abstract_excerpt":"State-of-the-art i-vector based speaker verification relies on variants of Probabilistic Linear Discriminant Analysis (PLDA) for discriminant analysis. We are mainly motivated by the recent work of the joint Bayesian (JB) method, which is originally proposed for discriminant analysis in face verification. We apply JB to speaker verification and make three contributions beyond the original JB. 1) In contrast to the EM iterations with approximated statistics in the original JB, the EM iterations with exact statistics are employed and give better performance. 2) We propose to do simultaneous diag"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1612.04056","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2016-12-13T08:13:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"caf0b45c877e5b612ee241b1c924ad4d327647bdf83a973ff81638d371e52fc5","abstract_canon_sha256":"0da9d757c7ba4bf8786aeede01ff8903562b0e5471bdadc6a46a471df28a6d85"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:52:30.709104Z","signature_b64":"OrscU7yQk7aj799hky1qQ0wQ4tK49jw1rN9KGRh2VAQqncSXwDlehbJWJQKl3B1GGI0Xada/NhUfjg6I2XQYAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"01a21dd0bfce83760824fa541f989020421f4f190f4637fc991205102b8b78c2","last_reissued_at":"2026-05-18T00:52:30.708701Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:52:30.708701Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Joint Bayesian Gaussian discriminant analysis for speaker verification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SD","authors_text":"Haotian Xu, Yiyan Wang, Zhijian Ou","submitted_at":"2016-12-13T08:13:03Z","abstract_excerpt":"State-of-the-art i-vector based speaker verification relies on variants of Probabilistic Linear Discriminant Analysis (PLDA) for discriminant analysis. We are mainly motivated by the recent work of the joint Bayesian (JB) method, which is originally proposed for discriminant analysis in face verification. We apply JB to speaker verification and make three contributions beyond the original JB. 1) In contrast to the EM iterations with approximated statistics in the original JB, the EM iterations with exact statistics are employed and give better performance. 2) We propose to do simultaneous diag"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.04056","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1612.04056","created_at":"2026-05-18T00:52:30.708755+00:00"},{"alias_kind":"arxiv_version","alias_value":"1612.04056v2","created_at":"2026-05-18T00:52:30.708755+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.04056","created_at":"2026-05-18T00:52:30.708755+00:00"},{"alias_kind":"pith_short_12","alias_value":"AGRB3UF7Z2BX","created_at":"2026-05-18T12:30:07.202191+00:00"},{"alias_kind":"pith_short_16","alias_value":"AGRB3UF7Z2BXMCBE","created_at":"2026-05-18T12:30:07.202191+00:00"},{"alias_kind":"pith_short_8","alias_value":"AGRB3UF7","created_at":"2026-05-18T12:30:07.202191+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/AGRB3UF7Z2BXMCBE7JKB7GEQEB","json":"https://pith.science/pith/AGRB3UF7Z2BXMCBE7JKB7GEQEB.json","graph_json":"https://pith.science/api/pith-number/AGRB3UF7Z2BXMCBE7JKB7GEQEB/graph.json","events_json":"https://pith.science/api/pith-number/AGRB3UF7Z2BXMCBE7JKB7GEQEB/events.json","paper":"https://pith.science/paper/AGRB3UF7"},"agent_actions":{"view_html":"https://pith.science/pith/AGRB3UF7Z2BXMCBE7JKB7GEQEB","download_json":"https://pith.science/pith/AGRB3UF7Z2BXMCBE7JKB7GEQEB.json","view_paper":"https://pith.science/paper/AGRB3UF7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1612.04056&json=true","fetch_graph":"https://pith.science/api/pith-number/AGRB3UF7Z2BXMCBE7JKB7GEQEB/graph.json","fetch_events":"https://pith.science/api/pith-number/AGRB3UF7Z2BXMCBE7JKB7GEQEB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AGRB3UF7Z2BXMCBE7JKB7GEQEB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AGRB3UF7Z2BXMCBE7JKB7GEQEB/action/storage_attestation","attest_author":"https://pith.science/pith/AGRB3UF7Z2BXMCBE7JKB7GEQEB/action/author_attestation","sign_citation":"https://pith.science/pith/AGRB3UF7Z2BXMCBE7JKB7GEQEB/action/citation_signature","submit_replication":"https://pith.science/pith/AGRB3UF7Z2BXMCBE7JKB7GEQEB/action/replication_record"}},"created_at":"2026-05-18T00:52:30.708755+00:00","updated_at":"2026-05-18T00:52:30.708755+00:00"}