{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:A6EZVKYNTEUO2PLTFUDA7ZAYVO","short_pith_number":"pith:A6EZVKYN","schema_version":"1.0","canonical_sha256":"07899aab0d9928ed3d732d060fe418abbe2c3ac556b3cf7fdb5f498281cec2c7","source":{"kind":"arxiv","id":"2203.07960","version":1},"attestation_state":"computed","paper":{"title":"Investigating self-supervised learning for speech enhancement and separation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.AS","authors_text":"Paola Garcia, Sanjeev Khudanpur, Shinji Watanabe, Shu-wen Yang, Zili Huang","submitted_at":"2022-03-15T14:43:02Z","abstract_excerpt":"Speech enhancement and separation are two fundamental tasks for robust speech processing. Speech enhancement suppresses background noise while speech separation extracts target speech from interfering speakers. Despite a great number of supervised learning-based enhancement and separation methods having been proposed and achieving good performance, studies on applying self-supervised learning (SSL) to enhancement and separation are limited. In this paper, we evaluate 13 SSL upstream methods on speech enhancement and separation downstream tasks. Our experimental results on Voicebank-DEMAND and "},"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":"2203.07960","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-03-15T14:43:02Z","cross_cats_sorted":[],"title_canon_sha256":"63c28eb9459403f63decde8938356c77a3217dcaea631f371ee00abc459ef007","abstract_canon_sha256":"4e726ad799ceaa4f9b4b46a4a4cc31a6cbb4cac499fdca02fc54025facde39e2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:05:24.570369Z","signature_b64":"RtryYAUX08s0xjdEVqthQOETebqCRfT58ZCxRj2gvJZ7E4Q/LQR8ALcQuUctaRH39muMDRDt/4SyeRodJyQLCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"07899aab0d9928ed3d732d060fe418abbe2c3ac556b3cf7fdb5f498281cec2c7","last_reissued_at":"2026-07-05T04:05:24.569950Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:05:24.569950Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Investigating self-supervised learning for speech enhancement and separation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.AS","authors_text":"Paola Garcia, Sanjeev Khudanpur, Shinji Watanabe, Shu-wen Yang, Zili Huang","submitted_at":"2022-03-15T14:43:02Z","abstract_excerpt":"Speech enhancement and separation are two fundamental tasks for robust speech processing. Speech enhancement suppresses background noise while speech separation extracts target speech from interfering speakers. Despite a great number of supervised learning-based enhancement and separation methods having been proposed and achieving good performance, studies on applying self-supervised learning (SSL) to enhancement and separation are limited. In this paper, we evaluate 13 SSL upstream methods on speech enhancement and separation downstream tasks. Our experimental results on Voicebank-DEMAND and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.07960","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/2203.07960/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":"2203.07960","created_at":"2026-07-05T04:05:24.570007+00:00"},{"alias_kind":"arxiv_version","alias_value":"2203.07960v1","created_at":"2026-07-05T04:05:24.570007+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.07960","created_at":"2026-07-05T04:05:24.570007+00:00"},{"alias_kind":"pith_short_12","alias_value":"A6EZVKYNTEUO","created_at":"2026-07-05T04:05:24.570007+00:00"},{"alias_kind":"pith_short_16","alias_value":"A6EZVKYNTEUO2PLT","created_at":"2026-07-05T04:05:24.570007+00:00"},{"alias_kind":"pith_short_8","alias_value":"A6EZVKYN","created_at":"2026-07-05T04:05:24.570007+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/A6EZVKYNTEUO2PLTFUDA7ZAYVO","json":"https://pith.science/pith/A6EZVKYNTEUO2PLTFUDA7ZAYVO.json","graph_json":"https://pith.science/api/pith-number/A6EZVKYNTEUO2PLTFUDA7ZAYVO/graph.json","events_json":"https://pith.science/api/pith-number/A6EZVKYNTEUO2PLTFUDA7ZAYVO/events.json","paper":"https://pith.science/paper/A6EZVKYN"},"agent_actions":{"view_html":"https://pith.science/pith/A6EZVKYNTEUO2PLTFUDA7ZAYVO","download_json":"https://pith.science/pith/A6EZVKYNTEUO2PLTFUDA7ZAYVO.json","view_paper":"https://pith.science/paper/A6EZVKYN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2203.07960&json=true","fetch_graph":"https://pith.science/api/pith-number/A6EZVKYNTEUO2PLTFUDA7ZAYVO/graph.json","fetch_events":"https://pith.science/api/pith-number/A6EZVKYNTEUO2PLTFUDA7ZAYVO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/A6EZVKYNTEUO2PLTFUDA7ZAYVO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/A6EZVKYNTEUO2PLTFUDA7ZAYVO/action/storage_attestation","attest_author":"https://pith.science/pith/A6EZVKYNTEUO2PLTFUDA7ZAYVO/action/author_attestation","sign_citation":"https://pith.science/pith/A6EZVKYNTEUO2PLTFUDA7ZAYVO/action/citation_signature","submit_replication":"https://pith.science/pith/A6EZVKYNTEUO2PLTFUDA7ZAYVO/action/replication_record"}},"created_at":"2026-07-05T04:05:24.570007+00:00","updated_at":"2026-07-05T04:05:24.570007+00:00"}