{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:VTBPDFVT6EJ5PX77ZAXUCLGLOJ","short_pith_number":"pith:VTBPDFVT","schema_version":"1.0","canonical_sha256":"acc2f196b3f113d7dfffc82f412ccb727b267b4cbaa9540f202d4db79b5b6d30","source":{"kind":"arxiv","id":"1907.12908","version":1},"attestation_state":"computed","paper":{"title":"Detecting Spoofing Attacks Using VGG and SincNet: BUT-Omilia Submission to ASVspoof 2019 Challenge","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CR"],"primary_cat":"cs.CV","authors_text":"Georgia Athanasopoulou, Hossein Zeinali, Ioannis Gkinis, Jan \"Honza'' \\v{C}ernock\\'y, Johan Rohdin, Luk\\'a\\v{s} Burget, Themos Stafylakis","submitted_at":"2019-07-13T17:27:40Z","abstract_excerpt":"In this paper, we present the system description of the joint efforts of Brno University of Technology (BUT) and Omilia -- Conversational Intelligence for the ASVSpoof2019 Spoofing and Countermeasures Challenge. The primary submission for Physical access (PA) is a fusion of two VGG networks, trained on single and two-channels features. For Logical access (LA), our primary system is a fusion of VGG and the recently introduced SincNet architecture. The results on PA show that the proposed networks yield very competitive performance in all conditions and achieved 86\\:\\% relative improvement compa"},"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":"1907.12908","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-13T17:27:40Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"b6e982c444c3b6f665b84d9c61b70bf6bd16bf0fc4f909ccd6063c94663ccb22","abstract_canon_sha256":"fbabfb573e635fd853dce088b863feb9f05215c91dcb36779bc5a4cbe236ea3e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:50:25.726972Z","signature_b64":"WtrXz42Y6ejahx3iKS0CRjuO9hJw23YmJ7FAGoYrulrJFNOlIGcvTmtafLC+2Kr1m8z1OpaUyvpvB0bp9PyWCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"acc2f196b3f113d7dfffc82f412ccb727b267b4cbaa9540f202d4db79b5b6d30","last_reissued_at":"2026-07-04T23:50:25.726418Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:50:25.726418Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Detecting Spoofing Attacks Using VGG and SincNet: BUT-Omilia Submission to ASVspoof 2019 Challenge","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CR"],"primary_cat":"cs.CV","authors_text":"Georgia Athanasopoulou, Hossein Zeinali, Ioannis Gkinis, Jan \"Honza'' \\v{C}ernock\\'y, Johan Rohdin, Luk\\'a\\v{s} Burget, Themos Stafylakis","submitted_at":"2019-07-13T17:27:40Z","abstract_excerpt":"In this paper, we present the system description of the joint efforts of Brno University of Technology (BUT) and Omilia -- Conversational Intelligence for the ASVSpoof2019 Spoofing and Countermeasures Challenge. The primary submission for Physical access (PA) is a fusion of two VGG networks, trained on single and two-channels features. For Logical access (LA), our primary system is a fusion of VGG and the recently introduced SincNet architecture. The results on PA show that the proposed networks yield very competitive performance in all conditions and achieved 86\\:\\% relative improvement compa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.12908","kind":"arxiv","version":1},"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/1907.12908/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":"1907.12908","created_at":"2026-07-04T23:50:25.726484+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.12908v1","created_at":"2026-07-04T23:50:25.726484+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.12908","created_at":"2026-07-04T23:50:25.726484+00:00"},{"alias_kind":"pith_short_12","alias_value":"VTBPDFVT6EJ5","created_at":"2026-07-04T23:50:25.726484+00:00"},{"alias_kind":"pith_short_16","alias_value":"VTBPDFVT6EJ5PX77","created_at":"2026-07-04T23:50:25.726484+00:00"},{"alias_kind":"pith_short_8","alias_value":"VTBPDFVT","created_at":"2026-07-04T23:50:25.726484+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2411.19841","citing_title":"Parallel Stacked Aggregated Network for Voice Authentication in IoT-Enabled Smart Devices","ref_index":59,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VTBPDFVT6EJ5PX77ZAXUCLGLOJ","json":"https://pith.science/pith/VTBPDFVT6EJ5PX77ZAXUCLGLOJ.json","graph_json":"https://pith.science/api/pith-number/VTBPDFVT6EJ5PX77ZAXUCLGLOJ/graph.json","events_json":"https://pith.science/api/pith-number/VTBPDFVT6EJ5PX77ZAXUCLGLOJ/events.json","paper":"https://pith.science/paper/VTBPDFVT"},"agent_actions":{"view_html":"https://pith.science/pith/VTBPDFVT6EJ5PX77ZAXUCLGLOJ","download_json":"https://pith.science/pith/VTBPDFVT6EJ5PX77ZAXUCLGLOJ.json","view_paper":"https://pith.science/paper/VTBPDFVT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.12908&json=true","fetch_graph":"https://pith.science/api/pith-number/VTBPDFVT6EJ5PX77ZAXUCLGLOJ/graph.json","fetch_events":"https://pith.science/api/pith-number/VTBPDFVT6EJ5PX77ZAXUCLGLOJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VTBPDFVT6EJ5PX77ZAXUCLGLOJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VTBPDFVT6EJ5PX77ZAXUCLGLOJ/action/storage_attestation","attest_author":"https://pith.science/pith/VTBPDFVT6EJ5PX77ZAXUCLGLOJ/action/author_attestation","sign_citation":"https://pith.science/pith/VTBPDFVT6EJ5PX77ZAXUCLGLOJ/action/citation_signature","submit_replication":"https://pith.science/pith/VTBPDFVT6EJ5PX77ZAXUCLGLOJ/action/replication_record"}},"created_at":"2026-07-04T23:50:25.726484+00:00","updated_at":"2026-07-04T23:50:25.726484+00:00"}