{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:UCPSG2YDJ6TF5EKMSBU2NJUUJI","short_pith_number":"pith:UCPSG2YD","canonical_record":{"source":{"id":"2010.14269","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-10-27T13:10:51Z","cross_cats_sorted":["cs.LG","eess.AS"],"title_canon_sha256":"f3e4608cf8b5eec7fcc76e4619a7f920395e72ad1016dec9534f12546a7320a0","abstract_canon_sha256":"852c880684b13cae17ac0fc9fd313ab223f6c62b51cb1c9456ac22808766c8a4"},"schema_version":"1.0"},"canonical_sha256":"a09f236b034fa65e914c9069a6a6944a1cca9df258ef0ec490df1b95e5905038","source":{"kind":"arxiv","id":"2010.14269","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.14269","created_at":"2026-07-05T02:34:30Z"},{"alias_kind":"arxiv_version","alias_value":"2010.14269v2","created_at":"2026-07-05T02:34:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.14269","created_at":"2026-07-05T02:34:30Z"},{"alias_kind":"pith_short_12","alias_value":"UCPSG2YDJ6TF","created_at":"2026-07-05T02:34:30Z"},{"alias_kind":"pith_short_16","alias_value":"UCPSG2YDJ6TF5EKM","created_at":"2026-07-05T02:34:30Z"},{"alias_kind":"pith_short_8","alias_value":"UCPSG2YD","created_at":"2026-07-05T02:34:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:UCPSG2YDJ6TF5EKMSBU2NJUUJI","target":"record","payload":{"canonical_record":{"source":{"id":"2010.14269","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-10-27T13:10:51Z","cross_cats_sorted":["cs.LG","eess.AS"],"title_canon_sha256":"f3e4608cf8b5eec7fcc76e4619a7f920395e72ad1016dec9534f12546a7320a0","abstract_canon_sha256":"852c880684b13cae17ac0fc9fd313ab223f6c62b51cb1c9456ac22808766c8a4"},"schema_version":"1.0"},"canonical_sha256":"a09f236b034fa65e914c9069a6a6944a1cca9df258ef0ec490df1b95e5905038","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:34:30.467099Z","signature_b64":"xFHU8Qz1g2cETOQ+h7b5c8AZT2L2aaxCNU+lPbyDTY5XY3iVNJCHuMu/M81h4XbgW8OPTfPJ669aIQsOWeNpAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a09f236b034fa65e914c9069a6a6944a1cca9df258ef0ec490df1b95e5905038","last_reissued_at":"2026-07-05T02:34:30.466528Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:34:30.466528Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.14269","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:34:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YuDFLxjrbKFHjgDCBGQND0insCUWY6y7wxP62kmLAATPhFggNSBeU2yGRtdDB4Od//61DGqqhF7mciki313vBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T12:34:04.191104Z"},"content_sha256":"bd066e5a9b25bd4ddfbdd6bcddc3901de47d7dc86e2226391c4c31ecce16b80d","schema_version":"1.0","event_id":"sha256:bd066e5a9b25bd4ddfbdd6bcddc3901de47d7dc86e2226391c4c31ecce16b80d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:UCPSG2YDJ6TF5EKMSBU2NJUUJI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Leveraging speaker attribute information using multi task learning for speaker verification and diarization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.AS"],"primary_cat":"cs.SD","authors_text":"Chau Luu, Peter Bell, Steve Renals","submitted_at":"2020-10-27T13:10:51Z","abstract_excerpt":"Deep speaker embeddings have become the leading method for encoding speaker identity in speaker recognition tasks. The embedding space should ideally capture the variations between all possible speakers, encoding the multiple acoustic aspects that make up a speaker's identity, whilst being robust to non-speaker acoustic variation. Deep speaker embeddings are normally trained discriminatively, predicting speaker identity labels on the training data. We hypothesise that additionally predicting speaker-related auxiliary variables -- such as age and nationality -- may yield representations that ar"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.14269","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2010.14269/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:34:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jLz3QhpqC1n4BoPTp9oC0uNEobjrPsl9g6dyBf/xzDMrnJy1Wse3FeHqLS6ddp8LogNr1KK44qYWQaXGRne+CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T12:34:04.191622Z"},"content_sha256":"92a619ce0427bb2e1dd0a379c7dd4c6a98fee4392373ab0321df9d76da0b0989","schema_version":"1.0","event_id":"sha256:92a619ce0427bb2e1dd0a379c7dd4c6a98fee4392373ab0321df9d76da0b0989"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UCPSG2YDJ6TF5EKMSBU2NJUUJI/bundle.json","state_url":"https://pith.science/pith/UCPSG2YDJ6TF5EKMSBU2NJUUJI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UCPSG2YDJ6TF5EKMSBU2NJUUJI/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-10T12:34:04Z","links":{"resolver":"https://pith.science/pith/UCPSG2YDJ6TF5EKMSBU2NJUUJI","bundle":"https://pith.science/pith/UCPSG2YDJ6TF5EKMSBU2NJUUJI/bundle.json","state":"https://pith.science/pith/UCPSG2YDJ6TF5EKMSBU2NJUUJI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UCPSG2YDJ6TF5EKMSBU2NJUUJI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:UCPSG2YDJ6TF5EKMSBU2NJUUJI","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":"852c880684b13cae17ac0fc9fd313ab223f6c62b51cb1c9456ac22808766c8a4","cross_cats_sorted":["cs.LG","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-10-27T13:10:51Z","title_canon_sha256":"f3e4608cf8b5eec7fcc76e4619a7f920395e72ad1016dec9534f12546a7320a0"},"schema_version":"1.0","source":{"id":"2010.14269","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.14269","created_at":"2026-07-05T02:34:30Z"},{"alias_kind":"arxiv_version","alias_value":"2010.14269v2","created_at":"2026-07-05T02:34:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.14269","created_at":"2026-07-05T02:34:30Z"},{"alias_kind":"pith_short_12","alias_value":"UCPSG2YDJ6TF","created_at":"2026-07-05T02:34:30Z"},{"alias_kind":"pith_short_16","alias_value":"UCPSG2YDJ6TF5EKM","created_at":"2026-07-05T02:34:30Z"},{"alias_kind":"pith_short_8","alias_value":"UCPSG2YD","created_at":"2026-07-05T02:34:30Z"}],"graph_snapshots":[{"event_id":"sha256:92a619ce0427bb2e1dd0a379c7dd4c6a98fee4392373ab0321df9d76da0b0989","target":"graph","created_at":"2026-07-05T02:34:30Z","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/2010.14269/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep speaker embeddings have become the leading method for encoding speaker identity in speaker recognition tasks. The embedding space should ideally capture the variations between all possible speakers, encoding the multiple acoustic aspects that make up a speaker's identity, whilst being robust to non-speaker acoustic variation. Deep speaker embeddings are normally trained discriminatively, predicting speaker identity labels on the training data. We hypothesise that additionally predicting speaker-related auxiliary variables -- such as age and nationality -- may yield representations that ar","authors_text":"Chau Luu, Peter Bell, Steve Renals","cross_cats":["cs.LG","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-10-27T13:10:51Z","title":"Leveraging speaker attribute information using multi task learning for speaker verification and diarization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.14269","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:bd066e5a9b25bd4ddfbdd6bcddc3901de47d7dc86e2226391c4c31ecce16b80d","target":"record","created_at":"2026-07-05T02:34:30Z","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":"852c880684b13cae17ac0fc9fd313ab223f6c62b51cb1c9456ac22808766c8a4","cross_cats_sorted":["cs.LG","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-10-27T13:10:51Z","title_canon_sha256":"f3e4608cf8b5eec7fcc76e4619a7f920395e72ad1016dec9534f12546a7320a0"},"schema_version":"1.0","source":{"id":"2010.14269","kind":"arxiv","version":2}},"canonical_sha256":"a09f236b034fa65e914c9069a6a6944a1cca9df258ef0ec490df1b95e5905038","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a09f236b034fa65e914c9069a6a6944a1cca9df258ef0ec490df1b95e5905038","first_computed_at":"2026-07-05T02:34:30.466528Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:34:30.466528Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xFHU8Qz1g2cETOQ+h7b5c8AZT2L2aaxCNU+lPbyDTY5XY3iVNJCHuMu/M81h4XbgW8OPTfPJ669aIQsOWeNpAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:34:30.467099Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.14269","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bd066e5a9b25bd4ddfbdd6bcddc3901de47d7dc86e2226391c4c31ecce16b80d","sha256:92a619ce0427bb2e1dd0a379c7dd4c6a98fee4392373ab0321df9d76da0b0989"],"state_sha256":"a0d02ebd605c55b617ec1a61ee00f69b92c15b81e5edae9942c92e6463775d1d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"86A1vustLa00BIfHjTDQgrGvrERFfdCwT5+A6KfDKgM0tu5EYMnNubOHTM5vlizH3bXLkial0HCWI45ZJdD+Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T12:34:04.197961Z","bundle_sha256":"81153151b9589baa6c6300200d1ba49ea48f995caa1d69cc8036f26295326f08"}}