{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:PI5UMFTSVXJLT2IQRAYN7HIJZP","short_pith_number":"pith:PI5UMFTS","canonical_record":{"source":{"id":"2401.07882","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-01-15T18:23:12Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"555b7c10f3096f394204f32c8dd61c26dfd1eb1c4e9bd52b1a907a6854e7576a","abstract_canon_sha256":"38e3a97a9c5398fe470d6b960fd667147919e2767f1c42bc8ff3cb5702d092f1"},"schema_version":"1.0"},"canonical_sha256":"7a3b461672add2b9e9108830df9d09cbfcd5e331147e2b1c29dd6e76cc5ae22d","source":{"kind":"arxiv","id":"2401.07882","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.07882","created_at":"2026-07-05T07:34:04Z"},{"alias_kind":"arxiv_version","alias_value":"2401.07882v1","created_at":"2026-07-05T07:34:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.07882","created_at":"2026-07-05T07:34:04Z"},{"alias_kind":"pith_short_12","alias_value":"PI5UMFTSVXJL","created_at":"2026-07-05T07:34:04Z"},{"alias_kind":"pith_short_16","alias_value":"PI5UMFTSVXJLT2IQ","created_at":"2026-07-05T07:34:04Z"},{"alias_kind":"pith_short_8","alias_value":"PI5UMFTS","created_at":"2026-07-05T07:34:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:PI5UMFTSVXJLT2IQRAYN7HIJZP","target":"record","payload":{"canonical_record":{"source":{"id":"2401.07882","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-01-15T18:23:12Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"555b7c10f3096f394204f32c8dd61c26dfd1eb1c4e9bd52b1a907a6854e7576a","abstract_canon_sha256":"38e3a97a9c5398fe470d6b960fd667147919e2767f1c42bc8ff3cb5702d092f1"},"schema_version":"1.0"},"canonical_sha256":"7a3b461672add2b9e9108830df9d09cbfcd5e331147e2b1c29dd6e76cc5ae22d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:34:04.024168Z","signature_b64":"7qqGm1ApLAb8C1mJQZybrHL5r06m/OgYZwHQSiXQPUeV+9cqhhLGQb28uj9DCkxYTsY3uhgBdNlHIJv9mPq7Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7a3b461672add2b9e9108830df9d09cbfcd5e331147e2b1c29dd6e76cc5ae22d","last_reissued_at":"2026-07-05T07:34:04.023828Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:34:04.023828Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.07882","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":"2026-07-05T07:34:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"61pejP+cSLh3oYz11MOADeaGwEH2z1ca4rFnJqWUR0oerfXVyjRxwsERjWxcTjjZv81HpP+2T4tP4iWmhCUjDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T20:22:04.706225Z"},"content_sha256":"df0d8a085e065ab31b38b55f4cb11e088f2ab5145695bca889a9fc982be0dca8","schema_version":"1.0","event_id":"sha256:df0d8a085e065ab31b38b55f4cb11e088f2ab5145695bca889a9fc982be0dca8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:PI5UMFTSVXJLT2IQRAYN7HIJZP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On the Importance of Neural Wiener Filter for Resource Efficient Multichannel Speech Enhancement","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.SD","authors_text":"Ashutosh Pandey, Buye Xu, Daniel Wong, Jacob Donley, Tsun-An Hsieh","submitted_at":"2024-01-15T18:23:12Z","abstract_excerpt":"We introduce a time-domain framework for efficient multichannel speech enhancement, emphasizing low latency and computational efficiency. This framework incorporates two compact deep neural networks (DNNs) surrounding a multichannel neural Wiener filter (NWF). The first DNN enhances the speech signal to estimate NWF coefficients, while the second DNN refines the output from the NWF. The NWF, while conceptually similar to the traditional frequency-domain Wiener filter, undergoes a training process optimized for low-latency speech enhancement, involving fine-tuning of both analysis and synthesis"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.07882","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/2401.07882/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":"2026-07-05T07:34:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aXfWyDelWk6Zbr9ZIIx6a7Kf05rxipVadNguW7J9f0l2DTz6XNFNxn34Z4twAceHFb36rU9LUa+S3r46MCi2Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T20:22:04.706615Z"},"content_sha256":"1e907d815fdde74a29c8e94ca1156302099b998c3a0c024ca80a140e9e696413","schema_version":"1.0","event_id":"sha256:1e907d815fdde74a29c8e94ca1156302099b998c3a0c024ca80a140e9e696413"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PI5UMFTSVXJLT2IQRAYN7HIJZP/bundle.json","state_url":"https://pith.science/pith/PI5UMFTSVXJLT2IQRAYN7HIJZP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PI5UMFTSVXJLT2IQRAYN7HIJZP/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":"2026-07-10T20:22:04Z","links":{"resolver":"https://pith.science/pith/PI5UMFTSVXJLT2IQRAYN7HIJZP","bundle":"https://pith.science/pith/PI5UMFTSVXJLT2IQRAYN7HIJZP/bundle.json","state":"https://pith.science/pith/PI5UMFTSVXJLT2IQRAYN7HIJZP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PI5UMFTSVXJLT2IQRAYN7HIJZP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PI5UMFTSVXJLT2IQRAYN7HIJZP","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":"38e3a97a9c5398fe470d6b960fd667147919e2767f1c42bc8ff3cb5702d092f1","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-01-15T18:23:12Z","title_canon_sha256":"555b7c10f3096f394204f32c8dd61c26dfd1eb1c4e9bd52b1a907a6854e7576a"},"schema_version":"1.0","source":{"id":"2401.07882","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.07882","created_at":"2026-07-05T07:34:04Z"},{"alias_kind":"arxiv_version","alias_value":"2401.07882v1","created_at":"2026-07-05T07:34:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.07882","created_at":"2026-07-05T07:34:04Z"},{"alias_kind":"pith_short_12","alias_value":"PI5UMFTSVXJL","created_at":"2026-07-05T07:34:04Z"},{"alias_kind":"pith_short_16","alias_value":"PI5UMFTSVXJLT2IQ","created_at":"2026-07-05T07:34:04Z"},{"alias_kind":"pith_short_8","alias_value":"PI5UMFTS","created_at":"2026-07-05T07:34:04Z"}],"graph_snapshots":[{"event_id":"sha256:1e907d815fdde74a29c8e94ca1156302099b998c3a0c024ca80a140e9e696413","target":"graph","created_at":"2026-07-05T07:34:04Z","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/2401.07882/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce a time-domain framework for efficient multichannel speech enhancement, emphasizing low latency and computational efficiency. This framework incorporates two compact deep neural networks (DNNs) surrounding a multichannel neural Wiener filter (NWF). The first DNN enhances the speech signal to estimate NWF coefficients, while the second DNN refines the output from the NWF. The NWF, while conceptually similar to the traditional frequency-domain Wiener filter, undergoes a training process optimized for low-latency speech enhancement, involving fine-tuning of both analysis and synthesis","authors_text":"Ashutosh Pandey, Buye Xu, Daniel Wong, Jacob Donley, Tsun-An Hsieh","cross_cats":["eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-01-15T18:23:12Z","title":"On the Importance of Neural Wiener Filter for Resource Efficient Multichannel Speech Enhancement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.07882","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:df0d8a085e065ab31b38b55f4cb11e088f2ab5145695bca889a9fc982be0dca8","target":"record","created_at":"2026-07-05T07:34:04Z","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":"38e3a97a9c5398fe470d6b960fd667147919e2767f1c42bc8ff3cb5702d092f1","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-01-15T18:23:12Z","title_canon_sha256":"555b7c10f3096f394204f32c8dd61c26dfd1eb1c4e9bd52b1a907a6854e7576a"},"schema_version":"1.0","source":{"id":"2401.07882","kind":"arxiv","version":1}},"canonical_sha256":"7a3b461672add2b9e9108830df9d09cbfcd5e331147e2b1c29dd6e76cc5ae22d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7a3b461672add2b9e9108830df9d09cbfcd5e331147e2b1c29dd6e76cc5ae22d","first_computed_at":"2026-07-05T07:34:04.023828Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:34:04.023828Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7qqGm1ApLAb8C1mJQZybrHL5r06m/OgYZwHQSiXQPUeV+9cqhhLGQb28uj9DCkxYTsY3uhgBdNlHIJv9mPq7Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:34:04.024168Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.07882","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:df0d8a085e065ab31b38b55f4cb11e088f2ab5145695bca889a9fc982be0dca8","sha256:1e907d815fdde74a29c8e94ca1156302099b998c3a0c024ca80a140e9e696413"],"state_sha256":"35eb0f59d7b55a0d236f763c2efa1a5a50230bf69064984abd78953c063dab44"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VY3Lqt+lwtNlwACRgBZS0I/BoKOelYWaOPCRYTACLjnk8yU8V73nSxVZa/CislSynJXoUxH24ytMpV1fVrowCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-10T20:22:04.708974Z","bundle_sha256":"52cf90b248ca1a4b86b2069ed339b0ee5712cd9a9034914a2330a6a80904e8af"}}