{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:WH53MLQRORDTJQ67CMBQCXTL64","short_pith_number":"pith:WH53MLQR","schema_version":"1.0","canonical_sha256":"b1fbb62e11744734c3df1303015e6bf717b692cac0dce3e936397c9ed240a2f8","source":{"kind":"arxiv","id":"2305.07347","version":1},"attestation_state":"computed","paper":{"title":"Music Rearrangement Using Hierarchical Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IR","cs.MM","eess.AS"],"primary_cat":"cs.SD","authors_text":"Christos Plachouras, Marius Miron","submitted_at":"2023-05-12T09:50:54Z","abstract_excerpt":"Music rearrangement involves reshuffling, deleting, and repeating sections of a music piece with the goal of producing a standalone version that has a different duration. It is a creative and time-consuming task commonly performed by an expert music engineer. In this paper, we propose a method for automatically rearranging music recordings that takes into account the hierarchical structure of the recording. Previous approaches focus solely on identifying cut-points in the audio that could result in smooth transitions. We instead utilize deep audio representations to hierarchically segment the "},"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":"2305.07347","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2023-05-12T09:50:54Z","cross_cats_sorted":["cs.IR","cs.MM","eess.AS"],"title_canon_sha256":"8dfaf650f99ce30a71cf8c51a54a8434c94a757741a7c83244ac8a2cc029bb4d","abstract_canon_sha256":"0313fe0047dbbe88ea30cd479590342a0d19125104d480e751e30f73138d66b8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:09:34.393373Z","signature_b64":"Aen3SGa1fivqfqbAVp2ogBD7Krr8gO8C1HJN2hpwNtxQo8EHUZd3oCgzKieo6EW6Dvr7nS5z8oOQmSOav2O6Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b1fbb62e11744734c3df1303015e6bf717b692cac0dce3e936397c9ed240a2f8","last_reissued_at":"2026-07-05T06:09:34.392938Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:09:34.392938Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Music Rearrangement Using Hierarchical Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IR","cs.MM","eess.AS"],"primary_cat":"cs.SD","authors_text":"Christos Plachouras, Marius Miron","submitted_at":"2023-05-12T09:50:54Z","abstract_excerpt":"Music rearrangement involves reshuffling, deleting, and repeating sections of a music piece with the goal of producing a standalone version that has a different duration. It is a creative and time-consuming task commonly performed by an expert music engineer. In this paper, we propose a method for automatically rearranging music recordings that takes into account the hierarchical structure of the recording. Previous approaches focus solely on identifying cut-points in the audio that could result in smooth transitions. We instead utilize deep audio representations to hierarchically segment the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.07347","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/2305.07347/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":"2305.07347","created_at":"2026-07-05T06:09:34.392994+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.07347v1","created_at":"2026-07-05T06:09:34.392994+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.07347","created_at":"2026-07-05T06:09:34.392994+00:00"},{"alias_kind":"pith_short_12","alias_value":"WH53MLQRORDT","created_at":"2026-07-05T06:09:34.392994+00:00"},{"alias_kind":"pith_short_16","alias_value":"WH53MLQRORDTJQ67","created_at":"2026-07-05T06:09:34.392994+00:00"},{"alias_kind":"pith_short_8","alias_value":"WH53MLQR","created_at":"2026-07-05T06:09:34.392994+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/WH53MLQRORDTJQ67CMBQCXTL64","json":"https://pith.science/pith/WH53MLQRORDTJQ67CMBQCXTL64.json","graph_json":"https://pith.science/api/pith-number/WH53MLQRORDTJQ67CMBQCXTL64/graph.json","events_json":"https://pith.science/api/pith-number/WH53MLQRORDTJQ67CMBQCXTL64/events.json","paper":"https://pith.science/paper/WH53MLQR"},"agent_actions":{"view_html":"https://pith.science/pith/WH53MLQRORDTJQ67CMBQCXTL64","download_json":"https://pith.science/pith/WH53MLQRORDTJQ67CMBQCXTL64.json","view_paper":"https://pith.science/paper/WH53MLQR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.07347&json=true","fetch_graph":"https://pith.science/api/pith-number/WH53MLQRORDTJQ67CMBQCXTL64/graph.json","fetch_events":"https://pith.science/api/pith-number/WH53MLQRORDTJQ67CMBQCXTL64/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WH53MLQRORDTJQ67CMBQCXTL64/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WH53MLQRORDTJQ67CMBQCXTL64/action/storage_attestation","attest_author":"https://pith.science/pith/WH53MLQRORDTJQ67CMBQCXTL64/action/author_attestation","sign_citation":"https://pith.science/pith/WH53MLQRORDTJQ67CMBQCXTL64/action/citation_signature","submit_replication":"https://pith.science/pith/WH53MLQRORDTJQ67CMBQCXTL64/action/replication_record"}},"created_at":"2026-07-05T06:09:34.392994+00:00","updated_at":"2026-07-05T06:09:34.392994+00:00"}