{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:IHKPEZATE2ICHZOX5YHHWQ7R7Z","short_pith_number":"pith:IHKPEZAT","schema_version":"1.0","canonical_sha256":"41d4f26413269023e5d7ee0e7b43f1fe7896b5297626508727dba47fe4d146ee","source":{"kind":"arxiv","id":"2211.10194","version":2},"attestation_state":"computed","paper":{"title":"Self-Remixing: Unsupervised Speech Separation via Separation and Remixing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Kohei Saijo, Tetsuji Ogawa","submitted_at":"2022-11-18T12:37:32Z","abstract_excerpt":"We present Self-Remixing, a novel self-supervised speech separation method, which refines a pre-trained separation model in an unsupervised manner. The proposed method consists of a shuffler module and a solver module, and they grow together through separation and remixing processes. Specifically, the shuffler first separates observed mixtures and makes pseudo-mixtures by shuffling and remixing the separated signals. The solver then separates the pseudo-mixtures and remixes the separated signals back to the observed mixtures. The solver is trained using the observed mixtures as supervision, wh"},"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":"2211.10194","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-11-18T12:37:32Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"2dc33b984f379677317f06321f5776136baf339fa0cce2404e9b0c1be17bc8d4","abstract_canon_sha256":"54611399340d0012fe9f7b6f1cfa4fc5bcd5eb6650c2abc06db2bdcebdf0e490"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:46:44.719115Z","signature_b64":"VEQOVw1t8HQ71macLL2CwBWQQ8Ajuz50DhHj7G3+Z3/2zQt/2f/vZspUTMNw/pAPRp/QRAK3RrjCSJB5XN7RBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"41d4f26413269023e5d7ee0e7b43f1fe7896b5297626508727dba47fe4d146ee","last_reissued_at":"2026-07-05T06:46:44.718596Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:46:44.718596Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Self-Remixing: Unsupervised Speech Separation via Separation and Remixing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Kohei Saijo, Tetsuji Ogawa","submitted_at":"2022-11-18T12:37:32Z","abstract_excerpt":"We present Self-Remixing, a novel self-supervised speech separation method, which refines a pre-trained separation model in an unsupervised manner. The proposed method consists of a shuffler module and a solver module, and they grow together through separation and remixing processes. Specifically, the shuffler first separates observed mixtures and makes pseudo-mixtures by shuffling and remixing the separated signals. The solver then separates the pseudo-mixtures and remixes the separated signals back to the observed mixtures. The solver is trained using the observed mixtures as supervision, wh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.10194","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/2211.10194/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":"2211.10194","created_at":"2026-07-05T06:46:44.718659+00:00"},{"alias_kind":"arxiv_version","alias_value":"2211.10194v2","created_at":"2026-07-05T06:46:44.718659+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.10194","created_at":"2026-07-05T06:46:44.718659+00:00"},{"alias_kind":"pith_short_12","alias_value":"IHKPEZATE2IC","created_at":"2026-07-05T06:46:44.718659+00:00"},{"alias_kind":"pith_short_16","alias_value":"IHKPEZATE2ICHZOX","created_at":"2026-07-05T06:46:44.718659+00:00"},{"alias_kind":"pith_short_8","alias_value":"IHKPEZAT","created_at":"2026-07-05T06:46:44.718659+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/IHKPEZATE2ICHZOX5YHHWQ7R7Z","json":"https://pith.science/pith/IHKPEZATE2ICHZOX5YHHWQ7R7Z.json","graph_json":"https://pith.science/api/pith-number/IHKPEZATE2ICHZOX5YHHWQ7R7Z/graph.json","events_json":"https://pith.science/api/pith-number/IHKPEZATE2ICHZOX5YHHWQ7R7Z/events.json","paper":"https://pith.science/paper/IHKPEZAT"},"agent_actions":{"view_html":"https://pith.science/pith/IHKPEZATE2ICHZOX5YHHWQ7R7Z","download_json":"https://pith.science/pith/IHKPEZATE2ICHZOX5YHHWQ7R7Z.json","view_paper":"https://pith.science/paper/IHKPEZAT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2211.10194&json=true","fetch_graph":"https://pith.science/api/pith-number/IHKPEZATE2ICHZOX5YHHWQ7R7Z/graph.json","fetch_events":"https://pith.science/api/pith-number/IHKPEZATE2ICHZOX5YHHWQ7R7Z/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IHKPEZATE2ICHZOX5YHHWQ7R7Z/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IHKPEZATE2ICHZOX5YHHWQ7R7Z/action/storage_attestation","attest_author":"https://pith.science/pith/IHKPEZATE2ICHZOX5YHHWQ7R7Z/action/author_attestation","sign_citation":"https://pith.science/pith/IHKPEZATE2ICHZOX5YHHWQ7R7Z/action/citation_signature","submit_replication":"https://pith.science/pith/IHKPEZATE2ICHZOX5YHHWQ7R7Z/action/replication_record"}},"created_at":"2026-07-05T06:46:44.718659+00:00","updated_at":"2026-07-05T06:46:44.718659+00:00"}