{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:UGNQKCH7MIWJAG2L3LKESD6AV2","short_pith_number":"pith:UGNQKCH7","canonical_record":{"source":{"id":"2607.11630","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2026-07-13T14:48:09Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"7bada4068067d5ee6c13c30df10b819d739901607c5ef6fee6e577b7920d762a","abstract_canon_sha256":"bb50a5c7f62b3c14ad12d608c66fc046f09d2cd3518472471434fce97b706d5e"},"schema_version":"1.0"},"canonical_sha256":"a19b0508ff622c901b4bdad4490fc0aeb2c138d6b61416b53c66cfa77d374034","source":{"kind":"arxiv","id":"2607.11630","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.11630","created_at":"2026-07-14T02:22:15Z"},{"alias_kind":"arxiv_version","alias_value":"2607.11630v1","created_at":"2026-07-14T02:22:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.11630","created_at":"2026-07-14T02:22:15Z"},{"alias_kind":"pith_short_12","alias_value":"UGNQKCH7MIWJ","created_at":"2026-07-14T02:22:15Z"},{"alias_kind":"pith_short_16","alias_value":"UGNQKCH7MIWJAG2L","created_at":"2026-07-14T02:22:15Z"},{"alias_kind":"pith_short_8","alias_value":"UGNQKCH7","created_at":"2026-07-14T02:22:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:UGNQKCH7MIWJAG2L3LKESD6AV2","target":"record","payload":{"canonical_record":{"source":{"id":"2607.11630","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2026-07-13T14:48:09Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"7bada4068067d5ee6c13c30df10b819d739901607c5ef6fee6e577b7920d762a","abstract_canon_sha256":"bb50a5c7f62b3c14ad12d608c66fc046f09d2cd3518472471434fce97b706d5e"},"schema_version":"1.0"},"canonical_sha256":"a19b0508ff622c901b4bdad4490fc0aeb2c138d6b61416b53c66cfa77d374034","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-14T02:22:15.767405Z","signature_b64":"nNFwgmfpZqa0X/TUaKnzsP8LweigCFk58tTJBxlbscxqqXjIvVsCrkGqY586sKGV1jEZyAxBAuttYpnGXn43BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a19b0508ff622c901b4bdad4490fc0aeb2c138d6b61416b53c66cfa77d374034","last_reissued_at":"2026-07-14T02:22:15.766610Z","signature_status":"signed_v1","first_computed_at":"2026-07-14T02:22:15.766610Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.11630","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-14T02:22:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QXJsW49dHprZ7kMukqVOepacLErXnA3LENHE5ZgJGOqmn0E7k/QPBmdlif/AWfQtIITW44pu4u8wrhZlIn0iDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T21:54:59.651260Z"},"content_sha256":"5dc3fd70d2375bc66c6afc6f6e4f8edea0268f1c9f29dfd706dce79b5b85de22","schema_version":"1.0","event_id":"sha256:5dc3fd70d2375bc66c6afc6f6e4f8edea0268f1c9f29dfd706dce79b5b85de22"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:UGNQKCH7MIWJAG2L3LKESD6AV2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Teaching Speech Enhancement Models to Sing: Domain Adaptation from Speech Enhancement to Singing Voice Separation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.SD","authors_text":"Alois Sontacchi, Mark D. Plumbley, Paul A. Bereuter","submitted_at":"2026-07-13T14:48:09Z","abstract_excerpt":"State-of-the-art speech enhancement models benefit from large-scale labeled datasets, whereas singing voice separation models suffer from limited available training data. To address this limitation, we formulate singing voice separation as domain adaptation from speech enhancement to singing voice separation. We investigate two fine-tuning strategies: full fine-tuning and parameter-efficient fine-tuning using Low-Rank Adaptation (LoRA) on a discriminative and a generative model. Models with either adaptation strategy outperform the same architectures trained from scratch by 0.29-1.8 dB in Sign"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.11630","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/2607.11630/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":"2026-07-14T02:22:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4Nzr4eOfnXBEFX4QsjfUMH2uAdI5hqkpas1IVcZSIzhP+Fd5VnfkwJmIaUUvubmUgnbalRlt5KOg5ouXinRXAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T21:54:59.651742Z"},"content_sha256":"0105d920be5322bbb95aacb8ea49e12b1ffb1081cc3cf285148cdd6607473c28","schema_version":"1.0","event_id":"sha256:0105d920be5322bbb95aacb8ea49e12b1ffb1081cc3cf285148cdd6607473c28"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UGNQKCH7MIWJAG2L3LKESD6AV2/bundle.json","state_url":"https://pith.science/pith/UGNQKCH7MIWJAG2L3LKESD6AV2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UGNQKCH7MIWJAG2L3LKESD6AV2/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":"2026-08-06T21:54:59Z","links":{"resolver":"https://pith.science/pith/UGNQKCH7MIWJAG2L3LKESD6AV2","bundle":"https://pith.science/pith/UGNQKCH7MIWJAG2L3LKESD6AV2/bundle.json","state":"https://pith.science/pith/UGNQKCH7MIWJAG2L3LKESD6AV2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UGNQKCH7MIWJAG2L3LKESD6AV2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:UGNQKCH7MIWJAG2L3LKESD6AV2","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":"bb50a5c7f62b3c14ad12d608c66fc046f09d2cd3518472471434fce97b706d5e","cross_cats_sorted":["eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2026-07-13T14:48:09Z","title_canon_sha256":"7bada4068067d5ee6c13c30df10b819d739901607c5ef6fee6e577b7920d762a"},"schema_version":"1.0","source":{"id":"2607.11630","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.11630","created_at":"2026-07-14T02:22:15Z"},{"alias_kind":"arxiv_version","alias_value":"2607.11630v1","created_at":"2026-07-14T02:22:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.11630","created_at":"2026-07-14T02:22:15Z"},{"alias_kind":"pith_short_12","alias_value":"UGNQKCH7MIWJ","created_at":"2026-07-14T02:22:15Z"},{"alias_kind":"pith_short_16","alias_value":"UGNQKCH7MIWJAG2L","created_at":"2026-07-14T02:22:15Z"},{"alias_kind":"pith_short_8","alias_value":"UGNQKCH7","created_at":"2026-07-14T02:22:15Z"}],"graph_snapshots":[{"event_id":"sha256:0105d920be5322bbb95aacb8ea49e12b1ffb1081cc3cf285148cdd6607473c28","target":"graph","created_at":"2026-07-14T02:22:15Z","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/2607.11630/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"State-of-the-art speech enhancement models benefit from large-scale labeled datasets, whereas singing voice separation models suffer from limited available training data. To address this limitation, we formulate singing voice separation as domain adaptation from speech enhancement to singing voice separation. We investigate two fine-tuning strategies: full fine-tuning and parameter-efficient fine-tuning using Low-Rank Adaptation (LoRA) on a discriminative and a generative model. Models with either adaptation strategy outperform the same architectures trained from scratch by 0.29-1.8 dB in Sign","authors_text":"Alois Sontacchi, Mark D. Plumbley, Paul A. Bereuter","cross_cats":["eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2026-07-13T14:48:09Z","title":"Teaching Speech Enhancement Models to Sing: Domain Adaptation from Speech Enhancement to Singing Voice Separation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.11630","kind":"arxiv","version":1},"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":"sha256:5dc3fd70d2375bc66c6afc6f6e4f8edea0268f1c9f29dfd706dce79b5b85de22","target":"record","created_at":"2026-07-14T02:22:15Z","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":"bb50a5c7f62b3c14ad12d608c66fc046f09d2cd3518472471434fce97b706d5e","cross_cats_sorted":["eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2026-07-13T14:48:09Z","title_canon_sha256":"7bada4068067d5ee6c13c30df10b819d739901607c5ef6fee6e577b7920d762a"},"schema_version":"1.0","source":{"id":"2607.11630","kind":"arxiv","version":1}},"canonical_sha256":"a19b0508ff622c901b4bdad4490fc0aeb2c138d6b61416b53c66cfa77d374034","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a19b0508ff622c901b4bdad4490fc0aeb2c138d6b61416b53c66cfa77d374034","first_computed_at":"2026-07-14T02:22:15.766610Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-14T02:22:15.766610Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nNFwgmfpZqa0X/TUaKnzsP8LweigCFk58tTJBxlbscxqqXjIvVsCrkGqY586sKGV1jEZyAxBAuttYpnGXn43BA==","signature_status":"signed_v1","signed_at":"2026-07-14T02:22:15.767405Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.11630","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5dc3fd70d2375bc66c6afc6f6e4f8edea0268f1c9f29dfd706dce79b5b85de22","sha256:0105d920be5322bbb95aacb8ea49e12b1ffb1081cc3cf285148cdd6607473c28"],"state_sha256":"9f37cc5a64c17f98020ebaba177fb4a0244acf95ae7243cad4db985617882bb8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"keNBfKJ+eWzc4tof8NIgnoh+UoSLJg4QXyKEjQ1E0YSrW7dJYkaTJWfNoTliDT20mU5DiJy7iNWWg91+/3S6Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T21:54:59.655308Z","bundle_sha256":"faa4cfe6f8468414d91860294d801e5ddfdeaff3e8b452235bfb1792a15e7743"}}