{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:CSUUMVDQNQ7P4FOYSPBOGH3CHJ","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":"bf763da9577556744407efce38427cae9ca995e934bf0785c63d718cc9d6fb0c","cross_cats_sorted":["cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2023-05-26T06:29:00Z","title_canon_sha256":"40a3a67ffbf124659a41649a6b2fe37dfd9292e20d559aefc42f7e3cf84dde67"},"schema_version":"1.0","source":{"id":"2305.16665","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.16665","created_at":"2026-07-05T06:59:52Z"},{"alias_kind":"arxiv_version","alias_value":"2305.16665v1","created_at":"2026-07-05T06:59:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.16665","created_at":"2026-07-05T06:59:52Z"},{"alias_kind":"pith_short_12","alias_value":"CSUUMVDQNQ7P","created_at":"2026-07-05T06:59:52Z"},{"alias_kind":"pith_short_16","alias_value":"CSUUMVDQNQ7P4FOY","created_at":"2026-07-05T06:59:52Z"},{"alias_kind":"pith_short_8","alias_value":"CSUUMVDQ","created_at":"2026-07-05T06:59:52Z"}],"graph_snapshots":[{"event_id":"sha256:9b8df32301d8ebef03a6d056c3f641bd43541fabe5c44502b2c8f4a7ae1edd01","target":"graph","created_at":"2026-07-05T06:59:52Z","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/2305.16665/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Noise suppression (NS) models have been widely applied to enhance speech quality. Recently, Deep Learning-Based NS, which we denote as Deep Noise Suppression (DNS), became the mainstream NS method due to its excelling performance over traditional ones. However, DNS models face 2 major challenges for supporting the real-world applications. First, high-performing DNS models are usually large in size, causing deployment difficulties. Second, DNS models require extensive training data, including noisy audios as inputs and clean audios as labels. It is often difficult to obtain clean labels for tra","authors_text":"Kai-Wei Chang, Xiulian Peng, Yan Lu, Yixin Wan, Yuan Zhou","cross_cats":["cs.SD"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2023-05-26T06:29:00Z","title":"ABC-KD: Attention-Based-Compression Knowledge Distillation for Deep Learning-Based Noise Suppression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.16665","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":"sha256:657920666bffd5a3f6680475bbbe25ad91efaef4c93c338d0c0be596ce7ffd70","target":"record","created_at":"2026-07-05T06:59:52Z","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":"bf763da9577556744407efce38427cae9ca995e934bf0785c63d718cc9d6fb0c","cross_cats_sorted":["cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2023-05-26T06:29:00Z","title_canon_sha256":"40a3a67ffbf124659a41649a6b2fe37dfd9292e20d559aefc42f7e3cf84dde67"},"schema_version":"1.0","source":{"id":"2305.16665","kind":"arxiv","version":1}},"canonical_sha256":"14a94654706c3efe15d893c2e31f623a591c2a2ce249ec283c30a15cf100eef1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"14a94654706c3efe15d893c2e31f623a591c2a2ce249ec283c30a15cf100eef1","first_computed_at":"2026-07-05T06:59:52.595510Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:59:52.595510Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N9UdDoNuuPb3TVaL4p6lSYctdLeOX4Ji3Tki9uJgcbHOmUXWFMJSE+pfpbp/83HfcV15wiP7QAzmZf7HHHVtCA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:59:52.595994Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.16665","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:657920666bffd5a3f6680475bbbe25ad91efaef4c93c338d0c0be596ce7ffd70","sha256:9b8df32301d8ebef03a6d056c3f641bd43541fabe5c44502b2c8f4a7ae1edd01"],"state_sha256":"594bd10eceb4d0e0d68077ca5656ddb4531a94d9ff47207cd502d5d83d121ed7"}