{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:Q2RJMFTQPLAVDJ2O6SENTRX56R","short_pith_number":"pith:Q2RJMFTQ","schema_version":"1.0","canonical_sha256":"86a29616707ac151a74ef488d9c6fdf46fcfb22a90f30bdb06e9b5086619543e","source":{"kind":"arxiv","id":"2409.17285","version":2},"attestation_state":"computed","paper":{"title":"SpoofCeleb: Speech Deepfake Detection and SASV In The Wild","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","eess.AS"],"primary_cat":"cs.SD","authors_text":"Hye-Jin Shim, Jee-weon Jung, Ji-Hoon Kim, Jinchuan Tian, Joon Son Chung, Nicholas Evans, Seyun Um, Shinji Watanabe, Shinnosuke Takamichi, Soumi Maiti, Wangyou Zhang, Xin Wang, Yihan Wu, Yuta Matsunaga","submitted_at":"2024-09-18T23:17:02Z","abstract_excerpt":"This paper introduces SpoofCeleb, a dataset designed for Speech Deepfake Detection (SDD) and Spoofing-robust Automatic Speaker Verification (SASV), utilizing source data from real-world conditions and spoofing attacks generated by Text-To-Speech (TTS) systems also trained on the same real-world data. Robust recognition systems require speech data recorded in varied acoustic environments with different levels of noise to be trained. However, current datasets typically include clean, high-quality recordings (bona fide data) due to the requirements for TTS training; studio-quality or well-recorde"},"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":"2409.17285","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-09-18T23:17:02Z","cross_cats_sorted":["cs.AI","eess.AS"],"title_canon_sha256":"68eeca12e149ebcc540f4c5be574841df08537a624975fe5df7b98af6afc1276","abstract_canon_sha256":"296e2921d516a7eaaa41dbf6d6777ff842d016b03b6a7f302ccd15ef23197a69"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:49:09.404901Z","signature_b64":"zj0FD8TEQVw8guXPyPTSYvWo8/Xisl2pXUcMrV/aSi98ZZl/wM+KCUgHgOrYUT6xWgRxJhjSngsZbuEA2/w4DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"86a29616707ac151a74ef488d9c6fdf46fcfb22a90f30bdb06e9b5086619543e","last_reissued_at":"2026-07-05T10:49:09.404438Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:49:09.404438Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SpoofCeleb: Speech Deepfake Detection and SASV In The Wild","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","eess.AS"],"primary_cat":"cs.SD","authors_text":"Hye-Jin Shim, Jee-weon Jung, Ji-Hoon Kim, Jinchuan Tian, Joon Son Chung, Nicholas Evans, Seyun Um, Shinji Watanabe, Shinnosuke Takamichi, Soumi Maiti, Wangyou Zhang, Xin Wang, Yihan Wu, Yuta Matsunaga","submitted_at":"2024-09-18T23:17:02Z","abstract_excerpt":"This paper introduces SpoofCeleb, a dataset designed for Speech Deepfake Detection (SDD) and Spoofing-robust Automatic Speaker Verification (SASV), utilizing source data from real-world conditions and spoofing attacks generated by Text-To-Speech (TTS) systems also trained on the same real-world data. Robust recognition systems require speech data recorded in varied acoustic environments with different levels of noise to be trained. However, current datasets typically include clean, high-quality recordings (bona fide data) due to the requirements for TTS training; studio-quality or well-recorde"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.17285","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/2409.17285/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2409.17285","created_at":"2026-07-05T10:49:09.404499+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.17285v2","created_at":"2026-07-05T10:49:09.404499+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.17285","created_at":"2026-07-05T10:49:09.404499+00:00"},{"alias_kind":"pith_short_12","alias_value":"Q2RJMFTQPLAV","created_at":"2026-07-05T10:49:09.404499+00:00"},{"alias_kind":"pith_short_16","alias_value":"Q2RJMFTQPLAVDJ2O","created_at":"2026-07-05T10:49:09.404499+00:00"},{"alias_kind":"pith_short_8","alias_value":"Q2RJMFTQ","created_at":"2026-07-05T10:49:09.404499+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/Q2RJMFTQPLAVDJ2O6SENTRX56R","json":"https://pith.science/pith/Q2RJMFTQPLAVDJ2O6SENTRX56R.json","graph_json":"https://pith.science/api/pith-number/Q2RJMFTQPLAVDJ2O6SENTRX56R/graph.json","events_json":"https://pith.science/api/pith-number/Q2RJMFTQPLAVDJ2O6SENTRX56R/events.json","paper":"https://pith.science/paper/Q2RJMFTQ"},"agent_actions":{"view_html":"https://pith.science/pith/Q2RJMFTQPLAVDJ2O6SENTRX56R","download_json":"https://pith.science/pith/Q2RJMFTQPLAVDJ2O6SENTRX56R.json","view_paper":"https://pith.science/paper/Q2RJMFTQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.17285&json=true","fetch_graph":"https://pith.science/api/pith-number/Q2RJMFTQPLAVDJ2O6SENTRX56R/graph.json","fetch_events":"https://pith.science/api/pith-number/Q2RJMFTQPLAVDJ2O6SENTRX56R/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Q2RJMFTQPLAVDJ2O6SENTRX56R/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Q2RJMFTQPLAVDJ2O6SENTRX56R/action/storage_attestation","attest_author":"https://pith.science/pith/Q2RJMFTQPLAVDJ2O6SENTRX56R/action/author_attestation","sign_citation":"https://pith.science/pith/Q2RJMFTQPLAVDJ2O6SENTRX56R/action/citation_signature","submit_replication":"https://pith.science/pith/Q2RJMFTQPLAVDJ2O6SENTRX56R/action/replication_record"}},"created_at":"2026-07-05T10:49:09.404499+00:00","updated_at":"2026-07-05T10:49:09.404499+00:00"}