{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:OXHSRRRYGQCPLLECC4LTHHV3Q7","short_pith_number":"pith:OXHSRRRY","schema_version":"1.0","canonical_sha256":"75cf28c6383404f5ac821717339ebb87c48bdbf991f4c41774cb42da778da3d5","source":{"kind":"arxiv","id":"2403.03538","version":1},"attestation_state":"computed","paper":{"title":"RADIA -- Radio Advertisement Detection with Intelligent Analytics","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","eess.AS"],"primary_cat":"cs.SD","authors_text":"Adri\\'an Alonso, Alfonso Ardoiz, Camilo Torr\\'on, Fernando Bay\\'on, Ignacio Arranz, Ignacio Garrido, \\'I\\~nigo Galdeano, Jorge \\'Alvarez, Juan Carlos Armenteros, Miguel Ortega-Mart\\'in, Oleg Vorontsov, \\'Oscar Garc\\'ia","submitted_at":"2024-03-06T08:34:28Z","abstract_excerpt":"Radio advertising remains an integral part of modern marketing strategies, with its appeal and potential for targeted reach undeniably effective. However, the dynamic nature of radio airtime and the rising trend of multiple radio spots necessitates an efficient system for monitoring advertisement broadcasts. This study investigates a novel automated radio advertisement detection technique incorporating advanced speech recognition and text classification algorithms. RadIA's approach surpasses traditional methods by eliminating the need for prior knowledge of the broadcast content. This contribu"},"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":"2403.03538","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.SD","submitted_at":"2024-03-06T08:34:28Z","cross_cats_sorted":["cs.AI","cs.CL","eess.AS"],"title_canon_sha256":"4cd9fa8529200e0b45cf71e01839028dc6a643735561f01ec600a50237d8f6bd","abstract_canon_sha256":"739136172a5afe288c7afbbd766fb9c5056eb8da98d6d045fb256245e164a154"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:53:00.828942Z","signature_b64":"FFXsjmYORo1eUjPO6ke7P1W+9dbo8hAhJEUB2RsSYYANxJ1q3txmVa/vo4exrA4kcQuVNM1oKxiBZZg2HY4NCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"75cf28c6383404f5ac821717339ebb87c48bdbf991f4c41774cb42da778da3d5","last_reissued_at":"2026-07-05T07:53:00.828567Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:53:00.828567Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RADIA -- Radio Advertisement Detection with Intelligent Analytics","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","eess.AS"],"primary_cat":"cs.SD","authors_text":"Adri\\'an Alonso, Alfonso Ardoiz, Camilo Torr\\'on, Fernando Bay\\'on, Ignacio Arranz, Ignacio Garrido, \\'I\\~nigo Galdeano, Jorge \\'Alvarez, Juan Carlos Armenteros, Miguel Ortega-Mart\\'in, Oleg Vorontsov, \\'Oscar Garc\\'ia","submitted_at":"2024-03-06T08:34:28Z","abstract_excerpt":"Radio advertising remains an integral part of modern marketing strategies, with its appeal and potential for targeted reach undeniably effective. However, the dynamic nature of radio airtime and the rising trend of multiple radio spots necessitates an efficient system for monitoring advertisement broadcasts. This study investigates a novel automated radio advertisement detection technique incorporating advanced speech recognition and text classification algorithms. RadIA's approach surpasses traditional methods by eliminating the need for prior knowledge of the broadcast content. This contribu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.03538","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/2403.03538/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":"2403.03538","created_at":"2026-07-05T07:53:00.828626+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.03538v1","created_at":"2026-07-05T07:53:00.828626+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.03538","created_at":"2026-07-05T07:53:00.828626+00:00"},{"alias_kind":"pith_short_12","alias_value":"OXHSRRRYGQCP","created_at":"2026-07-05T07:53:00.828626+00:00"},{"alias_kind":"pith_short_16","alias_value":"OXHSRRRYGQCPLLEC","created_at":"2026-07-05T07:53:00.828626+00:00"},{"alias_kind":"pith_short_8","alias_value":"OXHSRRRY","created_at":"2026-07-05T07:53:00.828626+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/OXHSRRRYGQCPLLECC4LTHHV3Q7","json":"https://pith.science/pith/OXHSRRRYGQCPLLECC4LTHHV3Q7.json","graph_json":"https://pith.science/api/pith-number/OXHSRRRYGQCPLLECC4LTHHV3Q7/graph.json","events_json":"https://pith.science/api/pith-number/OXHSRRRYGQCPLLECC4LTHHV3Q7/events.json","paper":"https://pith.science/paper/OXHSRRRY"},"agent_actions":{"view_html":"https://pith.science/pith/OXHSRRRYGQCPLLECC4LTHHV3Q7","download_json":"https://pith.science/pith/OXHSRRRYGQCPLLECC4LTHHV3Q7.json","view_paper":"https://pith.science/paper/OXHSRRRY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.03538&json=true","fetch_graph":"https://pith.science/api/pith-number/OXHSRRRYGQCPLLECC4LTHHV3Q7/graph.json","fetch_events":"https://pith.science/api/pith-number/OXHSRRRYGQCPLLECC4LTHHV3Q7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OXHSRRRYGQCPLLECC4LTHHV3Q7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OXHSRRRYGQCPLLECC4LTHHV3Q7/action/storage_attestation","attest_author":"https://pith.science/pith/OXHSRRRYGQCPLLECC4LTHHV3Q7/action/author_attestation","sign_citation":"https://pith.science/pith/OXHSRRRYGQCPLLECC4LTHHV3Q7/action/citation_signature","submit_replication":"https://pith.science/pith/OXHSRRRYGQCPLLECC4LTHHV3Q7/action/replication_record"}},"created_at":"2026-07-05T07:53:00.828626+00:00","updated_at":"2026-07-05T07:53:00.828626+00:00"}