{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:NIXR74DDKNDEYXH4FUGJT365IX","short_pith_number":"pith:NIXR74DD","canonical_record":{"source":{"id":"1712.02116","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-12-06T10:12:46Z","cross_cats_sorted":["cs.LG","eess.AS"],"title_canon_sha256":"0bd4f69eab828ab4dd3f0796058a6f3c440566eb34fc07becf8a4c1197302f33","abstract_canon_sha256":"411adb2879863be2824d6fc75927a7a3b16c7800380c99bfcb456e3c70991744"},"schema_version":"1.0"},"canonical_sha256":"6a2f1ff06353464c5cfc2d0c99efdd45ea1470058b126abacfced3dfc35ac80c","source":{"kind":"arxiv","id":"1712.02116","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.02116","created_at":"2026-05-17T23:49:17Z"},{"alias_kind":"arxiv_version","alias_value":"1712.02116v2","created_at":"2026-05-17T23:49:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.02116","created_at":"2026-05-17T23:49:17Z"},{"alias_kind":"pith_short_12","alias_value":"NIXR74DDKNDE","created_at":"2026-05-18T12:31:31Z"},{"alias_kind":"pith_short_16","alias_value":"NIXR74DDKNDEYXH4","created_at":"2026-05-18T12:31:31Z"},{"alias_kind":"pith_short_8","alias_value":"NIXR74DD","created_at":"2026-05-18T12:31:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:NIXR74DDKNDEYXH4FUGJT365IX","target":"record","payload":{"canonical_record":{"source":{"id":"1712.02116","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-12-06T10:12:46Z","cross_cats_sorted":["cs.LG","eess.AS"],"title_canon_sha256":"0bd4f69eab828ab4dd3f0796058a6f3c440566eb34fc07becf8a4c1197302f33","abstract_canon_sha256":"411adb2879863be2824d6fc75927a7a3b16c7800380c99bfcb456e3c70991744"},"schema_version":"1.0"},"canonical_sha256":"6a2f1ff06353464c5cfc2d0c99efdd45ea1470058b126abacfced3dfc35ac80c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:49:17.876148Z","signature_b64":"io8u73fSiZooPRJxRRPIat+CL6JWSakaZYM5Q9To/+GjagHKmRzHAWleMia6DHE2sPrJrAEH0jCtGzDEfjk5Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6a2f1ff06353464c5cfc2d0c99efdd45ea1470058b126abacfced3dfc35ac80c","last_reissued_at":"2026-05-17T23:49:17.875472Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:49:17.875472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.02116","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":"2026-05-17T23:49:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ng7BOI+1Aj0OERihDtyEyqSavOVxN8ouebEB6n0/4zfUCJ37f1Aj8JiXrC7iSpnYRWK97fG6/g8akZCptOG0Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T16:39:33.770240Z"},"content_sha256":"6bdb693e222c09cd31a10d23aa2fb26088d96cfc19b9aafcd3e19f0acb8eee96","schema_version":"1.0","event_id":"sha256:6bdb693e222c09cd31a10d23aa2fb26088d96cfc19b9aafcd3e19f0acb8eee96"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:NIXR74DDKNDEYXH4FUGJT365IX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Enabling Early Audio Event Detection with Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.AS"],"primary_cat":"cs.SD","authors_text":"Alfred Mertins, Huy Phan, Ian McLoughlin, Philipp Koch","submitted_at":"2017-12-06T10:12:46Z","abstract_excerpt":"This paper presents a methodology for early detection of audio events from audio streams. Early detection is the ability to infer an ongoing event during its initial stage. The proposed system consists of a novel inference step coupled with dual parallel tailored-loss deep neural networks (DNNs). The DNNs share a similar architecture except for their loss functions, i.e. weighted loss and multitask loss, which are designed to efficiently cope with issues common to audio event detection. The inference step is newly introduced to make use of the network outputs for recognizing ongoing events. Th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.02116","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":"2026-05-17T23:49:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VxEwqKrVRn0W7FjRw5nqVBtCiYD69yZLaueSqMBcQmq6R697JFby49ZZ/Lk003k9yEwXS2AesPbaraWbKGclCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T16:39:33.770881Z"},"content_sha256":"b9e02c06c0b9d252186ec34a82dac19cd0761f8b2f9b68e0261a20f7d3c7a8cf","schema_version":"1.0","event_id":"sha256:b9e02c06c0b9d252186ec34a82dac19cd0761f8b2f9b68e0261a20f7d3c7a8cf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NIXR74DDKNDEYXH4FUGJT365IX/bundle.json","state_url":"https://pith.science/pith/NIXR74DDKNDEYXH4FUGJT365IX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NIXR74DDKNDEYXH4FUGJT365IX/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":"2026-06-07T16:39:33Z","links":{"resolver":"https://pith.science/pith/NIXR74DDKNDEYXH4FUGJT365IX","bundle":"https://pith.science/pith/NIXR74DDKNDEYXH4FUGJT365IX/bundle.json","state":"https://pith.science/pith/NIXR74DDKNDEYXH4FUGJT365IX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NIXR74DDKNDEYXH4FUGJT365IX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:NIXR74DDKNDEYXH4FUGJT365IX","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":"411adb2879863be2824d6fc75927a7a3b16c7800380c99bfcb456e3c70991744","cross_cats_sorted":["cs.LG","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-12-06T10:12:46Z","title_canon_sha256":"0bd4f69eab828ab4dd3f0796058a6f3c440566eb34fc07becf8a4c1197302f33"},"schema_version":"1.0","source":{"id":"1712.02116","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.02116","created_at":"2026-05-17T23:49:17Z"},{"alias_kind":"arxiv_version","alias_value":"1712.02116v2","created_at":"2026-05-17T23:49:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.02116","created_at":"2026-05-17T23:49:17Z"},{"alias_kind":"pith_short_12","alias_value":"NIXR74DDKNDE","created_at":"2026-05-18T12:31:31Z"},{"alias_kind":"pith_short_16","alias_value":"NIXR74DDKNDEYXH4","created_at":"2026-05-18T12:31:31Z"},{"alias_kind":"pith_short_8","alias_value":"NIXR74DD","created_at":"2026-05-18T12:31:31Z"}],"graph_snapshots":[{"event_id":"sha256:b9e02c06c0b9d252186ec34a82dac19cd0761f8b2f9b68e0261a20f7d3c7a8cf","target":"graph","created_at":"2026-05-17T23:49:17Z","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":"This paper presents a methodology for early detection of audio events from audio streams. Early detection is the ability to infer an ongoing event during its initial stage. The proposed system consists of a novel inference step coupled with dual parallel tailored-loss deep neural networks (DNNs). The DNNs share a similar architecture except for their loss functions, i.e. weighted loss and multitask loss, which are designed to efficiently cope with issues common to audio event detection. The inference step is newly introduced to make use of the network outputs for recognizing ongoing events. Th","authors_text":"Alfred Mertins, Huy Phan, Ian McLoughlin, Philipp Koch","cross_cats":["cs.LG","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-12-06T10:12:46Z","title":"Enabling Early Audio Event Detection with Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.02116","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":"sha256:6bdb693e222c09cd31a10d23aa2fb26088d96cfc19b9aafcd3e19f0acb8eee96","target":"record","created_at":"2026-05-17T23:49:17Z","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":"411adb2879863be2824d6fc75927a7a3b16c7800380c99bfcb456e3c70991744","cross_cats_sorted":["cs.LG","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-12-06T10:12:46Z","title_canon_sha256":"0bd4f69eab828ab4dd3f0796058a6f3c440566eb34fc07becf8a4c1197302f33"},"schema_version":"1.0","source":{"id":"1712.02116","kind":"arxiv","version":2}},"canonical_sha256":"6a2f1ff06353464c5cfc2d0c99efdd45ea1470058b126abacfced3dfc35ac80c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6a2f1ff06353464c5cfc2d0c99efdd45ea1470058b126abacfced3dfc35ac80c","first_computed_at":"2026-05-17T23:49:17.875472Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:49:17.875472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"io8u73fSiZooPRJxRRPIat+CL6JWSakaZYM5Q9To/+GjagHKmRzHAWleMia6DHE2sPrJrAEH0jCtGzDEfjk5Dw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:49:17.876148Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.02116","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6bdb693e222c09cd31a10d23aa2fb26088d96cfc19b9aafcd3e19f0acb8eee96","sha256:b9e02c06c0b9d252186ec34a82dac19cd0761f8b2f9b68e0261a20f7d3c7a8cf"],"state_sha256":"c9c6eea144cd5866ce30b041e1526914b3d29dc4e28e758b87ffa5d3708a6f1b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"21hHrbP4kkgaYsbzJXz+j48TSYe49HNdC/hCGhNI1vpUSOxVuIBiwuxL5xmuGCspc2+rcEvHJtZi3lqMDFzzCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T16:39:33.774708Z","bundle_sha256":"56e9eb1bb06762488f562de41d1d4fd2734ab22985070d8a7f1ab33a486c6820"}}