{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:MX37KNFSOISA2TQQHHQQLBYKFJ","short_pith_number":"pith:MX37KNFS","canonical_record":{"source":{"id":"1802.10495","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-02-28T16:02:47Z","cross_cats_sorted":["cs.AI","cs.MM","cs.SD"],"title_canon_sha256":"43576b7ecb82802e213f959cd6cc7afe1906c7791c0a69e26bc27375e25e1110","abstract_canon_sha256":"c32da3350da1b581a974ee71c124994e0bb319437e34390fd66ef1c6a8dc293a"},"schema_version":"1.0"},"canonical_sha256":"65f7f534b272240d4e1039e105870a2a68d9c89414fd22b022aac97ff44150f2","source":{"kind":"arxiv","id":"1802.10495","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10495","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10495v2","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10495","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"pith_short_12","alias_value":"MX37KNFSOISA","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_16","alias_value":"MX37KNFSOISA2TQQ","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_8","alias_value":"MX37KNFS","created_at":"2026-05-18T12:32:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:MX37KNFSOISA2TQQHHQQLBYKFJ","target":"record","payload":{"canonical_record":{"source":{"id":"1802.10495","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-02-28T16:02:47Z","cross_cats_sorted":["cs.AI","cs.MM","cs.SD"],"title_canon_sha256":"43576b7ecb82802e213f959cd6cc7afe1906c7791c0a69e26bc27375e25e1110","abstract_canon_sha256":"c32da3350da1b581a974ee71c124994e0bb319437e34390fd66ef1c6a8dc293a"},"schema_version":"1.0"},"canonical_sha256":"65f7f534b272240d4e1039e105870a2a68d9c89414fd22b022aac97ff44150f2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:44.951055Z","signature_b64":"+UDQHkRGH6kOUR8uSd7YOa35tIRkje97MT7i26j4gJJY4LnKRSN12MZ7a6nQs4dSRcyV1rP6c2jI91b6ijIhAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"65f7f534b272240d4e1039e105870a2a68d9c89414fd22b022aac97ff44150f2","last_reissued_at":"2026-05-18T00:04:44.950369Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:44.950369Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.10495","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":"2026-05-18T00:04:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YwpV4kSFJPQ32ln5sCGlx9cZF7uBBjSDOL3WtNK8w5uigSiWx3VY/UMpkgWxvrlK8rz9HFfqcBw/7IX2brahCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T13:44:08.688108Z"},"content_sha256":"2faa622e7bebeeca1ed53854889a016ac8c4489c463cbc4f49251232c75dff70","schema_version":"1.0","event_id":"sha256:2faa622e7bebeeca1ed53854889a016ac8c4489c463cbc4f49251232c75dff70"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:MX37KNFSOISA2TQQHHQQLBYKFJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pop Music Highlighter: Marking the Emotion Keypoints","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.MM","cs.SD"],"primary_cat":"eess.AS","authors_text":"Szu-Yu Chou, Yi-Hsuan Yang, Yu-Siang Huang","submitted_at":"2018-02-28T16:02:47Z","abstract_excerpt":"The goal of music highlight extraction is to get a short consecutive segment of a piece of music that provides an effective representation of the whole piece. In a previous work, we introduced an attention-based convolutional recurrent neural network that uses music emotion classification as a surrogate task for music highlight extraction, for Pop songs. The rationale behind that approach is that the highlight of a song is usually the most emotional part. This paper extends our previous work in the following two aspects. First, methodology-wise we experiment with a new architecture that does n"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10495","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":"2026-05-18T00:04:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"adjcEWT2yHG9xr72nghGqIhZpfF5EVfAXTdtNzgeEQinDe2YS0G17FdD3UGy1FD/Y/uPHQ6uZ1Dim+g4wX8uDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T13:44:08.688837Z"},"content_sha256":"d204649ca9d7a7dc31a477166ee50c14c038041bb024fccf3bde25f391b47a11","schema_version":"1.0","event_id":"sha256:d204649ca9d7a7dc31a477166ee50c14c038041bb024fccf3bde25f391b47a11"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MX37KNFSOISA2TQQHHQQLBYKFJ/bundle.json","state_url":"https://pith.science/pith/MX37KNFSOISA2TQQHHQQLBYKFJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MX37KNFSOISA2TQQHHQQLBYKFJ/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":"2026-05-27T13:44:08Z","links":{"resolver":"https://pith.science/pith/MX37KNFSOISA2TQQHHQQLBYKFJ","bundle":"https://pith.science/pith/MX37KNFSOISA2TQQHHQQLBYKFJ/bundle.json","state":"https://pith.science/pith/MX37KNFSOISA2TQQHHQQLBYKFJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MX37KNFSOISA2TQQHHQQLBYKFJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:MX37KNFSOISA2TQQHHQQLBYKFJ","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":"c32da3350da1b581a974ee71c124994e0bb319437e34390fd66ef1c6a8dc293a","cross_cats_sorted":["cs.AI","cs.MM","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-02-28T16:02:47Z","title_canon_sha256":"43576b7ecb82802e213f959cd6cc7afe1906c7791c0a69e26bc27375e25e1110"},"schema_version":"1.0","source":{"id":"1802.10495","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10495","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10495v2","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10495","created_at":"2026-05-18T00:04:44Z"},{"alias_kind":"pith_short_12","alias_value":"MX37KNFSOISA","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_16","alias_value":"MX37KNFSOISA2TQQ","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_8","alias_value":"MX37KNFS","created_at":"2026-05-18T12:32:40Z"}],"graph_snapshots":[{"event_id":"sha256:d204649ca9d7a7dc31a477166ee50c14c038041bb024fccf3bde25f391b47a11","target":"graph","created_at":"2026-05-18T00:04:44Z","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":"The goal of music highlight extraction is to get a short consecutive segment of a piece of music that provides an effective representation of the whole piece. In a previous work, we introduced an attention-based convolutional recurrent neural network that uses music emotion classification as a surrogate task for music highlight extraction, for Pop songs. The rationale behind that approach is that the highlight of a song is usually the most emotional part. This paper extends our previous work in the following two aspects. First, methodology-wise we experiment with a new architecture that does n","authors_text":"Szu-Yu Chou, Yi-Hsuan Yang, Yu-Siang Huang","cross_cats":["cs.AI","cs.MM","cs.SD"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-02-28T16:02:47Z","title":"Pop Music Highlighter: Marking the Emotion Keypoints"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10495","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":"sha256:2faa622e7bebeeca1ed53854889a016ac8c4489c463cbc4f49251232c75dff70","target":"record","created_at":"2026-05-18T00:04:44Z","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":"c32da3350da1b581a974ee71c124994e0bb319437e34390fd66ef1c6a8dc293a","cross_cats_sorted":["cs.AI","cs.MM","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-02-28T16:02:47Z","title_canon_sha256":"43576b7ecb82802e213f959cd6cc7afe1906c7791c0a69e26bc27375e25e1110"},"schema_version":"1.0","source":{"id":"1802.10495","kind":"arxiv","version":2}},"canonical_sha256":"65f7f534b272240d4e1039e105870a2a68d9c89414fd22b022aac97ff44150f2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"65f7f534b272240d4e1039e105870a2a68d9c89414fd22b022aac97ff44150f2","first_computed_at":"2026-05-18T00:04:44.950369Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:04:44.950369Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+UDQHkRGH6kOUR8uSd7YOa35tIRkje97MT7i26j4gJJY4LnKRSN12MZ7a6nQs4dSRcyV1rP6c2jI91b6ijIhAg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:04:44.951055Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.10495","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2faa622e7bebeeca1ed53854889a016ac8c4489c463cbc4f49251232c75dff70","sha256:d204649ca9d7a7dc31a477166ee50c14c038041bb024fccf3bde25f391b47a11"],"state_sha256":"e3eec7a7f66523541ed7485848fedd591917904e24f7fe7f1e6a6bff9ced4b41"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h1Xumat0BmfT2/nAfuz29EJ20Mz+4L+TYgWvtq9eeREcUM6M69T6YD8Od1yR2wRbTXNfHZTKOKXS57H/tNjeAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T13:44:08.692762Z","bundle_sha256":"1e1ddc435f532d699171d2793fd79aeb75b1efc9c69c7a5852acd4a3bdd096a5"}}