{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:SP53RIVCSEVZVE3SYOYYV46LS3","short_pith_number":"pith:SP53RIVC","schema_version":"1.0","canonical_sha256":"93fbb8a2a2912b9a9372c3b18af3cb96cf0ad9a54f9727a826e400d2219c36dd","source":{"kind":"arxiv","id":"1904.03006","version":1},"attestation_state":"computed","paper":{"title":"Robust Binaural Localization of a Target Sound Source by Combining Spectral Source Models and Deep Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Guy J. Brown, Jose A. Gonzalez, Ning Ma","submitted_at":"2019-04-05T11:50:25Z","abstract_excerpt":"Despite there being clear evidence for top-down (e.g., attentional) effects in biological spatial hearing, relatively few machine hearing systems exploit top-down model-based knowledge in sound localisation. This paper addresses this issue by proposing a novel framework for binaural sound localisation that combines model-based information about the spectral characteristics of sound sources and deep neural networks (DNNs). A target source model and a background source model are first estimated during a training phase using spectral features extracted from sound signals in isolation. When the id"},"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":"1904.03006","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-04-05T11:50:25Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"afe1091b2b3e5f3759bf09f77e33dee0de5de9aa17a0589ec26e5367d15b2705","abstract_canon_sha256":"c32dabaa89eeadace7e4940620a0d0f7259047daed86cb39db11f25de154590f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:49:18.924070Z","signature_b64":"OVjvJu98OY24U3BwDQCZBRUuL7qHYYnCHGmbY2b3SBNIVJeOcNXNHgQYLG+KlmXIsIBMeJ/S/F1Rk0WCghowBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"93fbb8a2a2912b9a9372c3b18af3cb96cf0ad9a54f9727a826e400d2219c36dd","last_reissued_at":"2026-05-17T23:49:18.923429Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:49:18.923429Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Robust Binaural Localization of a Target Sound Source by Combining Spectral Source Models and Deep Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Guy J. Brown, Jose A. Gonzalez, Ning Ma","submitted_at":"2019-04-05T11:50:25Z","abstract_excerpt":"Despite there being clear evidence for top-down (e.g., attentional) effects in biological spatial hearing, relatively few machine hearing systems exploit top-down model-based knowledge in sound localisation. This paper addresses this issue by proposing a novel framework for binaural sound localisation that combines model-based information about the spectral characteristics of sound sources and deep neural networks (DNNs). A target source model and a background source model are first estimated during a training phase using spectral features extracted from sound signals in isolation. When the id"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.03006","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":""},"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":"1904.03006","created_at":"2026-05-17T23:49:18.923524+00:00"},{"alias_kind":"arxiv_version","alias_value":"1904.03006v1","created_at":"2026-05-17T23:49:18.923524+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.03006","created_at":"2026-05-17T23:49:18.923524+00:00"},{"alias_kind":"pith_short_12","alias_value":"SP53RIVCSEVZ","created_at":"2026-05-18T12:33:27.125529+00:00"},{"alias_kind":"pith_short_16","alias_value":"SP53RIVCSEVZVE3S","created_at":"2026-05-18T12:33:27.125529+00:00"},{"alias_kind":"pith_short_8","alias_value":"SP53RIVC","created_at":"2026-05-18T12:33:27.125529+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/SP53RIVCSEVZVE3SYOYYV46LS3","json":"https://pith.science/pith/SP53RIVCSEVZVE3SYOYYV46LS3.json","graph_json":"https://pith.science/api/pith-number/SP53RIVCSEVZVE3SYOYYV46LS3/graph.json","events_json":"https://pith.science/api/pith-number/SP53RIVCSEVZVE3SYOYYV46LS3/events.json","paper":"https://pith.science/paper/SP53RIVC"},"agent_actions":{"view_html":"https://pith.science/pith/SP53RIVCSEVZVE3SYOYYV46LS3","download_json":"https://pith.science/pith/SP53RIVCSEVZVE3SYOYYV46LS3.json","view_paper":"https://pith.science/paper/SP53RIVC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1904.03006&json=true","fetch_graph":"https://pith.science/api/pith-number/SP53RIVCSEVZVE3SYOYYV46LS3/graph.json","fetch_events":"https://pith.science/api/pith-number/SP53RIVCSEVZVE3SYOYYV46LS3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SP53RIVCSEVZVE3SYOYYV46LS3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SP53RIVCSEVZVE3SYOYYV46LS3/action/storage_attestation","attest_author":"https://pith.science/pith/SP53RIVCSEVZVE3SYOYYV46LS3/action/author_attestation","sign_citation":"https://pith.science/pith/SP53RIVCSEVZVE3SYOYYV46LS3/action/citation_signature","submit_replication":"https://pith.science/pith/SP53RIVCSEVZVE3SYOYYV46LS3/action/replication_record"}},"created_at":"2026-05-17T23:49:18.923524+00:00","updated_at":"2026-05-17T23:49:18.923524+00:00"}