{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:OYONTERHFHWN4Y6FMWDIAHQMO3","short_pith_number":"pith:OYONTERH","canonical_record":{"source":{"id":"2201.09592","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-01-24T11:05:30Z","cross_cats_sorted":["cs.AI","cs.LG","eess.AS"],"title_canon_sha256":"724fcbdd892624f6ead46f616da8d9291669f294155c25e0d98f6f67fd727058","abstract_canon_sha256":"58b2dc753572d5ad693f42a45443d0e47b4c99382c92d6f6f9f59869026ee86d"},"schema_version":"1.0"},"canonical_sha256":"761cd9922729ecde63c56586801e0c76c9b1d5192a979c352e09ea74aaf3ebda","source":{"kind":"arxiv","id":"2201.09592","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.09592","created_at":"2026-07-05T05:37:04Z"},{"alias_kind":"arxiv_version","alias_value":"2201.09592v2","created_at":"2026-07-05T05:37:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.09592","created_at":"2026-07-05T05:37:04Z"},{"alias_kind":"pith_short_12","alias_value":"OYONTERHFHWN","created_at":"2026-07-05T05:37:04Z"},{"alias_kind":"pith_short_16","alias_value":"OYONTERHFHWN4Y6F","created_at":"2026-07-05T05:37:04Z"},{"alias_kind":"pith_short_8","alias_value":"OYONTERH","created_at":"2026-07-05T05:37:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:OYONTERHFHWN4Y6FMWDIAHQMO3","target":"record","payload":{"canonical_record":{"source":{"id":"2201.09592","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-01-24T11:05:30Z","cross_cats_sorted":["cs.AI","cs.LG","eess.AS"],"title_canon_sha256":"724fcbdd892624f6ead46f616da8d9291669f294155c25e0d98f6f67fd727058","abstract_canon_sha256":"58b2dc753572d5ad693f42a45443d0e47b4c99382c92d6f6f9f59869026ee86d"},"schema_version":"1.0"},"canonical_sha256":"761cd9922729ecde63c56586801e0c76c9b1d5192a979c352e09ea74aaf3ebda","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:37:04.586273Z","signature_b64":"uNpYW6QcyMYjYmfMtWnoIy5+7Xp+h9odfgj+HYPgesWf65ofjhlMZf/iqzAo5ADRw9U7KhMpRToz/XwAncB0Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"761cd9922729ecde63c56586801e0c76c9b1d5192a979c352e09ea74aaf3ebda","last_reissued_at":"2026-07-05T05:37:04.585758Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:37:04.585758Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2201.09592","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":"2026-07-05T05:37:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W7SK/0p/WbUpHIu9dLOeaJALUoJCt+VSNhS9H+sfD8zBARhcQVY0NnA4gaHYIPeTxTRKeYueqwShs1aa07y/AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T08:57:13.990713Z"},"content_sha256":"3b5783e8fc1490a0088fd01a799140608be8efd93e8e8ac37e426e0bc1d150e5","schema_version":"1.0","event_id":"sha256:3b5783e8fc1490a0088fd01a799140608be8efd93e8e8ac37e426e0bc1d150e5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:OYONTERHFHWN4Y6FMWDIAHQMO3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Music Source Separation Using Differentiable Parametric Source Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG","eess.AS"],"primary_cat":"cs.SD","authors_text":"Clement S. J. Doire, Ga\\\"el Richard, Kilian Schulze-Forster, Liam Kelley, Roland Badeau","submitted_at":"2022-01-24T11:05:30Z","abstract_excerpt":"Supervised deep learning approaches to underdetermined audio source separation achieve state-of-the-art performance but require a dataset of mixtures along with their corresponding isolated source signals. Such datasets can be extremely costly to obtain for musical mixtures. This raises a need for unsupervised methods. We propose a novel unsupervised model-based deep learning approach to musical source separation. Each source is modelled with a differentiable parametric source-filter model. A neural network is trained to reconstruct the observed mixture as a sum of the sources by estimating th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.09592","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2201.09592/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:37:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D7pvmLqcOH8InVCp4QFONfDZmRL+82UXlGPmCYYQVUSeDUe2QmHOJW9ED86Wyvc99Zn6vL/L/hg+gxhMWgWnAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T08:57:13.991649Z"},"content_sha256":"44e8edb74071f2639c0a5186d1957c09e1a102fa1096cdd79d969f287cab0d7f","schema_version":"1.0","event_id":"sha256:44e8edb74071f2639c0a5186d1957c09e1a102fa1096cdd79d969f287cab0d7f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OYONTERHFHWN4Y6FMWDIAHQMO3/bundle.json","state_url":"https://pith.science/pith/OYONTERHFHWN4Y6FMWDIAHQMO3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OYONTERHFHWN4Y6FMWDIAHQMO3/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":"2026-08-21T08:57:13Z","links":{"resolver":"https://pith.science/pith/OYONTERHFHWN4Y6FMWDIAHQMO3","bundle":"https://pith.science/pith/OYONTERHFHWN4Y6FMWDIAHQMO3/bundle.json","state":"https://pith.science/pith/OYONTERHFHWN4Y6FMWDIAHQMO3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OYONTERHFHWN4Y6FMWDIAHQMO3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:OYONTERHFHWN4Y6FMWDIAHQMO3","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":"58b2dc753572d5ad693f42a45443d0e47b4c99382c92d6f6f9f59869026ee86d","cross_cats_sorted":["cs.AI","cs.LG","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-01-24T11:05:30Z","title_canon_sha256":"724fcbdd892624f6ead46f616da8d9291669f294155c25e0d98f6f67fd727058"},"schema_version":"1.0","source":{"id":"2201.09592","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.09592","created_at":"2026-07-05T05:37:04Z"},{"alias_kind":"arxiv_version","alias_value":"2201.09592v2","created_at":"2026-07-05T05:37:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.09592","created_at":"2026-07-05T05:37:04Z"},{"alias_kind":"pith_short_12","alias_value":"OYONTERHFHWN","created_at":"2026-07-05T05:37:04Z"},{"alias_kind":"pith_short_16","alias_value":"OYONTERHFHWN4Y6F","created_at":"2026-07-05T05:37:04Z"},{"alias_kind":"pith_short_8","alias_value":"OYONTERH","created_at":"2026-07-05T05:37:04Z"}],"graph_snapshots":[{"event_id":"sha256:44e8edb74071f2639c0a5186d1957c09e1a102fa1096cdd79d969f287cab0d7f","target":"graph","created_at":"2026-07-05T05:37:04Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2201.09592/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Supervised deep learning approaches to underdetermined audio source separation achieve state-of-the-art performance but require a dataset of mixtures along with their corresponding isolated source signals. Such datasets can be extremely costly to obtain for musical mixtures. This raises a need for unsupervised methods. We propose a novel unsupervised model-based deep learning approach to musical source separation. Each source is modelled with a differentiable parametric source-filter model. A neural network is trained to reconstruct the observed mixture as a sum of the sources by estimating th","authors_text":"Clement S. J. Doire, Ga\\\"el Richard, Kilian Schulze-Forster, Liam Kelley, Roland Badeau","cross_cats":["cs.AI","cs.LG","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-01-24T11:05:30Z","title":"Unsupervised Music Source Separation Using Differentiable Parametric Source Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.09592","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":"sha256:3b5783e8fc1490a0088fd01a799140608be8efd93e8e8ac37e426e0bc1d150e5","target":"record","created_at":"2026-07-05T05:37:04Z","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":"58b2dc753572d5ad693f42a45443d0e47b4c99382c92d6f6f9f59869026ee86d","cross_cats_sorted":["cs.AI","cs.LG","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-01-24T11:05:30Z","title_canon_sha256":"724fcbdd892624f6ead46f616da8d9291669f294155c25e0d98f6f67fd727058"},"schema_version":"1.0","source":{"id":"2201.09592","kind":"arxiv","version":2}},"canonical_sha256":"761cd9922729ecde63c56586801e0c76c9b1d5192a979c352e09ea74aaf3ebda","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"761cd9922729ecde63c56586801e0c76c9b1d5192a979c352e09ea74aaf3ebda","first_computed_at":"2026-07-05T05:37:04.585758Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:37:04.585758Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uNpYW6QcyMYjYmfMtWnoIy5+7Xp+h9odfgj+HYPgesWf65ofjhlMZf/iqzAo5ADRw9U7KhMpRToz/XwAncB0Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:37:04.586273Z","signed_message":"canonical_sha256_bytes"},"source_id":"2201.09592","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3b5783e8fc1490a0088fd01a799140608be8efd93e8e8ac37e426e0bc1d150e5","sha256:44e8edb74071f2639c0a5186d1957c09e1a102fa1096cdd79d969f287cab0d7f"],"state_sha256":"42fc4e6948c910952d3619f5623cd0eb23a1967b3dcccd4ff02fe367a0f149af"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EOv0ZDbFDFM8IXhIBAH9orwJJY0PQdRGGBFhqcftl0FI8ukMDSNqsa8ep7frFfvwCJHLuQ69CytVs4SJcVg1Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T08:57:14.001657Z","bundle_sha256":"006e9dfeee46d0337e4d2961479bbb1a33086a0c4344d573d44f526783f1dd5c"}}