{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:6PEIAXJGMGPYKLWGJSNRGJCICZ","short_pith_number":"pith:6PEIAXJG","canonical_record":{"source":{"id":"1709.08243","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-09-24T19:23:22Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"a588a32fb9b3113f0fd0ef4ad8eaba1c65910b5f06b0a56a2d7298d0302af8b1","abstract_canon_sha256":"4f75fdd510adde6add2dac243764f221cbd024559da36e4f952c9d7a49e8ffee"},"schema_version":"1.0"},"canonical_sha256":"f3c8805d26619f852ec64c9b13244816537e4715facb22e10ba21a57e4d8082b","source":{"kind":"arxiv","id":"1709.08243","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.08243","created_at":"2026-05-18T00:14:28Z"},{"alias_kind":"arxiv_version","alias_value":"1709.08243v3","created_at":"2026-05-18T00:14:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.08243","created_at":"2026-05-18T00:14:28Z"},{"alias_kind":"pith_short_12","alias_value":"6PEIAXJGMGPY","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"6PEIAXJGMGPYKLWG","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"6PEIAXJG","created_at":"2026-05-18T12:31:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:6PEIAXJGMGPYKLWGJSNRGJCICZ","target":"record","payload":{"canonical_record":{"source":{"id":"1709.08243","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-09-24T19:23:22Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"a588a32fb9b3113f0fd0ef4ad8eaba1c65910b5f06b0a56a2d7298d0302af8b1","abstract_canon_sha256":"4f75fdd510adde6add2dac243764f221cbd024559da36e4f952c9d7a49e8ffee"},"schema_version":"1.0"},"canonical_sha256":"f3c8805d26619f852ec64c9b13244816537e4715facb22e10ba21a57e4d8082b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:28.712572Z","signature_b64":"yq07vojGVKxJUBCPvLrI2e+4ugDCx2dXuZurufm6DkDhPJDDd60N1tx/xPwefswabcYZE5+RXuDHgsw4CG3KDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f3c8805d26619f852ec64c9b13244816537e4715facb22e10ba21a57e4d8082b","last_reissued_at":"2026-05-18T00:14:28.711868Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:28.711868Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.08243","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:14:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7A9P1m7IDIJ/m5hvc5JDHqwKR1Gce4h7eSNnI+VRYdmbavClayUKwL3hJsmVgQghlpM0X61yXcslxskBxmUIDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T03:48:51.868654Z"},"content_sha256":"1089c13ed5fa361facdc0a4c0c54c3d43025065e20f4fc667275cfa5b09ded11","schema_version":"1.0","event_id":"sha256:1089c13ed5fa361facdc0a4c0c54c3d43025065e20f4fc667275cfa5b09ded11"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:6PEIAXJGMGPYKLWGJSNRGJCICZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Hybrid DSP/Deep Learning Approach to Real-Time Full-Band Speech Enhancement","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.SD","authors_text":"Jean-Marc Valin","submitted_at":"2017-09-24T19:23:22Z","abstract_excerpt":"Despite noise suppression being a mature area in signal processing, it remains highly dependent on fine tuning of estimator algorithms and parameters. In this paper, we demonstrate a hybrid DSP/deep learning approach to noise suppression. A deep neural network with four hidden layers is used to estimate ideal critical band gains, while a more traditional pitch filter attenuates noise between pitch harmonics. The approach achieves significantly higher quality than a traditional minimum mean squared error spectral estimator, while keeping the complexity low enough for real-time operation at 48 k"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.08243","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-18T00:14:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/o9Qc533Fm0D8sTItSBCCsgr6dwGgt56wH/rnHUaOCBxeheawJ1JE1RXMlVRW4fUOsgEfA16oxJhaTg5/+a2Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T03:48:51.869256Z"},"content_sha256":"e46f501e5c41def147c9dcdd31cf64072279b8e69612582723d1fb95c19fa288","schema_version":"1.0","event_id":"sha256:e46f501e5c41def147c9dcdd31cf64072279b8e69612582723d1fb95c19fa288"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6PEIAXJGMGPYKLWGJSNRGJCICZ/bundle.json","state_url":"https://pith.science/pith/6PEIAXJGMGPYKLWGJSNRGJCICZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6PEIAXJGMGPYKLWGJSNRGJCICZ/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":"2026-08-05T03:48:51Z","links":{"resolver":"https://pith.science/pith/6PEIAXJGMGPYKLWGJSNRGJCICZ","bundle":"https://pith.science/pith/6PEIAXJGMGPYKLWGJSNRGJCICZ/bundle.json","state":"https://pith.science/pith/6PEIAXJGMGPYKLWGJSNRGJCICZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6PEIAXJGMGPYKLWGJSNRGJCICZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:6PEIAXJGMGPYKLWGJSNRGJCICZ","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":"4f75fdd510adde6add2dac243764f221cbd024559da36e4f952c9d7a49e8ffee","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-09-24T19:23:22Z","title_canon_sha256":"a588a32fb9b3113f0fd0ef4ad8eaba1c65910b5f06b0a56a2d7298d0302af8b1"},"schema_version":"1.0","source":{"id":"1709.08243","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.08243","created_at":"2026-05-18T00:14:28Z"},{"alias_kind":"arxiv_version","alias_value":"1709.08243v3","created_at":"2026-05-18T00:14:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.08243","created_at":"2026-05-18T00:14:28Z"},{"alias_kind":"pith_short_12","alias_value":"6PEIAXJGMGPY","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"6PEIAXJGMGPYKLWG","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"6PEIAXJG","created_at":"2026-05-18T12:31:03Z"}],"graph_snapshots":[{"event_id":"sha256:e46f501e5c41def147c9dcdd31cf64072279b8e69612582723d1fb95c19fa288","target":"graph","created_at":"2026-05-18T00:14:28Z","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"},"paper":{"abstract_excerpt":"Despite noise suppression being a mature area in signal processing, it remains highly dependent on fine tuning of estimator algorithms and parameters. In this paper, we demonstrate a hybrid DSP/deep learning approach to noise suppression. A deep neural network with four hidden layers is used to estimate ideal critical band gains, while a more traditional pitch filter attenuates noise between pitch harmonics. The approach achieves significantly higher quality than a traditional minimum mean squared error spectral estimator, while keeping the complexity low enough for real-time operation at 48 k","authors_text":"Jean-Marc Valin","cross_cats":["eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-09-24T19:23:22Z","title":"A Hybrid DSP/Deep Learning Approach to Real-Time Full-Band Speech Enhancement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.08243","kind":"arxiv","version":3},"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":"sha256:1089c13ed5fa361facdc0a4c0c54c3d43025065e20f4fc667275cfa5b09ded11","target":"record","created_at":"2026-05-18T00:14:28Z","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":"4f75fdd510adde6add2dac243764f221cbd024559da36e4f952c9d7a49e8ffee","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-09-24T19:23:22Z","title_canon_sha256":"a588a32fb9b3113f0fd0ef4ad8eaba1c65910b5f06b0a56a2d7298d0302af8b1"},"schema_version":"1.0","source":{"id":"1709.08243","kind":"arxiv","version":3}},"canonical_sha256":"f3c8805d26619f852ec64c9b13244816537e4715facb22e10ba21a57e4d8082b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f3c8805d26619f852ec64c9b13244816537e4715facb22e10ba21a57e4d8082b","first_computed_at":"2026-05-18T00:14:28.711868Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:28.711868Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yq07vojGVKxJUBCPvLrI2e+4ugDCx2dXuZurufm6DkDhPJDDd60N1tx/xPwefswabcYZE5+RXuDHgsw4CG3KDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:28.712572Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.08243","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1089c13ed5fa361facdc0a4c0c54c3d43025065e20f4fc667275cfa5b09ded11","sha256:e46f501e5c41def147c9dcdd31cf64072279b8e69612582723d1fb95c19fa288"],"state_sha256":"8fd53d21a9036b37c8f85e2d35adacf8880f761ff3a73ba32382244953e86a97"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pwZmkxhx0K9UgIsUFkK87ILVq9rgAOl/YJtsh8+js3eHKaI0KYaJjfcAIwWo6REblmKk/+yLqHOsMpjhAkFgAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T03:48:51.874733Z","bundle_sha256":"29615a163c137d449626757fc3d4a4adacc9f5c688d30bbe429cca2661a4d624"}}