{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:VTGAZ5P7QLXY4NV4DUIWGDBH63","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":"4d0ca808096c711856acba8b109bc33e746f1acb3d282d197cf6f99407f55bc9","cross_cats_sorted":["cs.LG","eess.AS","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-10-31T12:52:09Z","title_canon_sha256":"a577a1eef2efcec72a9778e892fe63ad8082a0d2cde3ae2f1892689dc5b9e5bb"},"schema_version":"1.0","source":{"id":"1710.11439","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.11439","created_at":"2026-05-17T23:51:44Z"},{"alias_kind":"arxiv_version","alias_value":"1710.11439v4","created_at":"2026-05-17T23:51:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.11439","created_at":"2026-05-17T23:51:44Z"},{"alias_kind":"pith_short_12","alias_value":"VTGAZ5P7QLXY","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VTGAZ5P7QLXY4NV4","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VTGAZ5P7","created_at":"2026-05-18T12:31:49Z"}],"graph_snapshots":[{"event_id":"sha256:d9529de109584cc96ddb600081a7f44f6a8752d438281b293aafa5ca6fc001e5","target":"graph","created_at":"2026-05-17T23:51:44Z","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":"This paper presents a statistical method of single-channel speech enhancement that uses a variational autoencoder (VAE) as a prior distribution on clean speech. A standard approach to speech enhancement is to train a deep neural network (DNN) to take noisy speech as input and output clean speech. Although this supervised approach requires a very large amount of pair data for training, it is not robust against unknown environments. Another approach is to use non-negative matrix factorization (NMF) based on basis spectra trained on clean speech in advance and those adapted to noise on the fly. T","authors_text":"Katsutoshi Itoyama, Kazuyoshi Yoshii, Masato Mimura, Tatsuya Kawahara, Yoshiaki Bando","cross_cats":["cs.LG","eess.AS","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-10-31T12:52:09Z","title":"Statistical Speech Enhancement Based on Probabilistic Integration of Variational Autoencoder and Non-Negative Matrix Factorization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.11439","kind":"arxiv","version":4},"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:cee060dab46f6f12a1ed726470f86aa57466e3305c9de9c0e15a6d1cc1d8f3ac","target":"record","created_at":"2026-05-17T23:51:44Z","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":"4d0ca808096c711856acba8b109bc33e746f1acb3d282d197cf6f99407f55bc9","cross_cats_sorted":["cs.LG","eess.AS","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-10-31T12:52:09Z","title_canon_sha256":"a577a1eef2efcec72a9778e892fe63ad8082a0d2cde3ae2f1892689dc5b9e5bb"},"schema_version":"1.0","source":{"id":"1710.11439","kind":"arxiv","version":4}},"canonical_sha256":"accc0cf5ff82ef8e36bc1d11630c27f6cac9bc6892bc7293e7b4966f8962d461","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"accc0cf5ff82ef8e36bc1d11630c27f6cac9bc6892bc7293e7b4966f8962d461","first_computed_at":"2026-05-17T23:51:44.439783Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:51:44.439783Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sY4ZNZMLD/6gDR8iXQNGesM3E7GJAEwUUIcZyLblxlQgTiuN5PPFTokriKyqX5eLk8oHATI4fisYTxWGs7sCCQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:51:44.440331Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.11439","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cee060dab46f6f12a1ed726470f86aa57466e3305c9de9c0e15a6d1cc1d8f3ac","sha256:d9529de109584cc96ddb600081a7f44f6a8752d438281b293aafa5ca6fc001e5"],"state_sha256":"bbe9abf1122afe794252f7bf7d227cf77fd086c52d7abb91409b110eec6e3588"}