{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:RJPKG6DUGTI6AATQPP5XBJB7EB","short_pith_number":"pith:RJPKG6DU","canonical_record":{"source":{"id":"1802.05792","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-15T23:24:39Z","cross_cats_sorted":["cs.SD","eess.AS","stat.ML"],"title_canon_sha256":"441635f944ab5fef7badf8aa2dc2e6d07f9c2f4764392a85037f2d76e720afce","abstract_canon_sha256":"3296e6b43b9daa12b91ca546c45d40cbee390f1d6586d6a57fa24d9693dbe52d"},"schema_version":"1.0"},"canonical_sha256":"8a5ea3787434d1e002707bfb70a43f20685927d430cb8d1a8b0059b9adc398fc","source":{"kind":"arxiv","id":"1802.05792","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.05792","created_at":"2026-05-17T23:47:40Z"},{"alias_kind":"arxiv_version","alias_value":"1802.05792v2","created_at":"2026-05-17T23:47:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.05792","created_at":"2026-05-17T23:47:40Z"},{"alias_kind":"pith_short_12","alias_value":"RJPKG6DUGTI6","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"RJPKG6DUGTI6AATQ","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"RJPKG6DU","created_at":"2026-05-18T12:32:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:RJPKG6DUGTI6AATQPP5XBJB7EB","target":"record","payload":{"canonical_record":{"source":{"id":"1802.05792","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-15T23:24:39Z","cross_cats_sorted":["cs.SD","eess.AS","stat.ML"],"title_canon_sha256":"441635f944ab5fef7badf8aa2dc2e6d07f9c2f4764392a85037f2d76e720afce","abstract_canon_sha256":"3296e6b43b9daa12b91ca546c45d40cbee390f1d6586d6a57fa24d9693dbe52d"},"schema_version":"1.0"},"canonical_sha256":"8a5ea3787434d1e002707bfb70a43f20685927d430cb8d1a8b0059b9adc398fc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:40.145475Z","signature_b64":"YF2BltBaxQjt9fxretuOOUl8NX5F9RtutKmhOoCpw0vT4Vf8xX8lJpj7WnB38GQeTCwwRUd58vq5/MPgz97rDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8a5ea3787434d1e002707bfb70a43f20685927d430cb8d1a8b0059b9adc398fc","last_reissued_at":"2026-05-17T23:47:40.145029Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:40.145029Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.05792","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":"2026-05-17T23:47:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BEIxN4M3Egw7Qwv46AESA7lnEyGEzsMZhgDYYXXi5KFOeFFAJ0h1SmgNOmJuWZ7k+LxmXoQ36lecBOPSpRKnDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T19:28:47.513281Z"},"content_sha256":"d30fe9b08f37a5af05751f70a8d0290030ebbbcf3c7123b9bb1ec195968215bc","schema_version":"1.0","event_id":"sha256:d30fe9b08f37a5af05751f70a8d0290030ebbbcf3c7123b9bb1ec195968215bc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:RJPKG6DUGTI6AATQPP5XBJB7EB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Masked Conditional Neural Networks for Automatic Sound Events Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SD","eess.AS","stat.ML"],"primary_cat":"cs.LG","authors_text":"David Chesmore, Fady Medhat, John Robinson","submitted_at":"2018-02-15T23:24:39Z","abstract_excerpt":"Deep neural network architectures designed for application domains other than sound, especially image recognition, may not optimally harness the time-frequency representation when adapted to the sound recognition problem. In this work, we explore the ConditionaL Neural Network (CLNN) and the Masked ConditionaL Neural Network (MCLNN) for multi-dimensional temporal signal recognition. The CLNN considers the inter-frame relationship, and the MCLNN enforces a systematic sparseness over the network's links to enable learning in frequency bands rather than bins allowing the network to be frequency s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.05792","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":""},"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":"2026-05-17T23:47:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gPHnRsetphgGbCb1aDTtFbt5v/sM/EuBYAZoDFTNwkTaCBkHHfIhlT0BaysbR/vZwi7dAh2KTlX3xUkwgt63DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T19:28:47.513661Z"},"content_sha256":"2460747bb238da0efc22fab9a505c827fc472e3305d000f5aaa4169fb2dae389","schema_version":"1.0","event_id":"sha256:2460747bb238da0efc22fab9a505c827fc472e3305d000f5aaa4169fb2dae389"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RJPKG6DUGTI6AATQPP5XBJB7EB/bundle.json","state_url":"https://pith.science/pith/RJPKG6DUGTI6AATQPP5XBJB7EB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RJPKG6DUGTI6AATQPP5XBJB7EB/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":"2026-06-04T19:28:47Z","links":{"resolver":"https://pith.science/pith/RJPKG6DUGTI6AATQPP5XBJB7EB","bundle":"https://pith.science/pith/RJPKG6DUGTI6AATQPP5XBJB7EB/bundle.json","state":"https://pith.science/pith/RJPKG6DUGTI6AATQPP5XBJB7EB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RJPKG6DUGTI6AATQPP5XBJB7EB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:RJPKG6DUGTI6AATQPP5XBJB7EB","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":"3296e6b43b9daa12b91ca546c45d40cbee390f1d6586d6a57fa24d9693dbe52d","cross_cats_sorted":["cs.SD","eess.AS","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-15T23:24:39Z","title_canon_sha256":"441635f944ab5fef7badf8aa2dc2e6d07f9c2f4764392a85037f2d76e720afce"},"schema_version":"1.0","source":{"id":"1802.05792","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.05792","created_at":"2026-05-17T23:47:40Z"},{"alias_kind":"arxiv_version","alias_value":"1802.05792v2","created_at":"2026-05-17T23:47:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.05792","created_at":"2026-05-17T23:47:40Z"},{"alias_kind":"pith_short_12","alias_value":"RJPKG6DUGTI6","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"RJPKG6DUGTI6AATQ","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"RJPKG6DU","created_at":"2026-05-18T12:32:50Z"}],"graph_snapshots":[{"event_id":"sha256:2460747bb238da0efc22fab9a505c827fc472e3305d000f5aaa4169fb2dae389","target":"graph","created_at":"2026-05-17T23:47:40Z","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"},"paper":{"abstract_excerpt":"Deep neural network architectures designed for application domains other than sound, especially image recognition, may not optimally harness the time-frequency representation when adapted to the sound recognition problem. In this work, we explore the ConditionaL Neural Network (CLNN) and the Masked ConditionaL Neural Network (MCLNN) for multi-dimensional temporal signal recognition. The CLNN considers the inter-frame relationship, and the MCLNN enforces a systematic sparseness over the network's links to enable learning in frequency bands rather than bins allowing the network to be frequency s","authors_text":"David Chesmore, Fady Medhat, John Robinson","cross_cats":["cs.SD","eess.AS","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-15T23:24:39Z","title":"Masked Conditional Neural Networks for Automatic Sound Events Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.05792","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:d30fe9b08f37a5af05751f70a8d0290030ebbbcf3c7123b9bb1ec195968215bc","target":"record","created_at":"2026-05-17T23:47:40Z","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":"3296e6b43b9daa12b91ca546c45d40cbee390f1d6586d6a57fa24d9693dbe52d","cross_cats_sorted":["cs.SD","eess.AS","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-15T23:24:39Z","title_canon_sha256":"441635f944ab5fef7badf8aa2dc2e6d07f9c2f4764392a85037f2d76e720afce"},"schema_version":"1.0","source":{"id":"1802.05792","kind":"arxiv","version":2}},"canonical_sha256":"8a5ea3787434d1e002707bfb70a43f20685927d430cb8d1a8b0059b9adc398fc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8a5ea3787434d1e002707bfb70a43f20685927d430cb8d1a8b0059b9adc398fc","first_computed_at":"2026-05-17T23:47:40.145029Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:47:40.145029Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YF2BltBaxQjt9fxretuOOUl8NX5F9RtutKmhOoCpw0vT4Vf8xX8lJpj7WnB38GQeTCwwRUd58vq5/MPgz97rDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:47:40.145475Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.05792","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d30fe9b08f37a5af05751f70a8d0290030ebbbcf3c7123b9bb1ec195968215bc","sha256:2460747bb238da0efc22fab9a505c827fc472e3305d000f5aaa4169fb2dae389"],"state_sha256":"95253720afb6c42700e0c57c957be83b2ead305206eb2c54cdd16df3a3c758b5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PedCwlV2TnzmdOsBzUdKKOakNqvp+EYsNJZMfaN+qHMx0lt4pe1YDRV0uSiJKMu6a7vvFCpG9gP2EFUitbDTDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T19:28:47.515709Z","bundle_sha256":"6254d48c9f4b0f4e02635593308be7277a1fb7152aa0885d594a5281a6633512"}}