{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:ZKW35BW3UDJVVDX32FREKD3EYW","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":"c3179546b9e8e1a020bc0c47169f9f63e22d648db1b8bb72f54b04eb7d3dba1c","cross_cats_sorted":["cs.LG","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-27T11:01:33Z","title_canon_sha256":"2bfa2aa3c6c0bec49f0e887012c5edef273dd879cac7dc2e5283c4bade5f4c6e"},"schema_version":"1.0","source":{"id":"1704.08504","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.08504","created_at":"2026-05-18T00:35:41Z"},{"alias_kind":"arxiv_version","alias_value":"1704.08504v2","created_at":"2026-05-18T00:35:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.08504","created_at":"2026-05-18T00:35:41Z"},{"alias_kind":"pith_short_12","alias_value":"ZKW35BW3UDJV","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZKW35BW3UDJVVDX3","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZKW35BW3","created_at":"2026-05-18T12:31:59Z"}],"graph_snapshots":[{"event_id":"sha256:61730f8b981ed55ac81de98421e32bdf366a04c84fa29bf06faef31199c5a729","target":"graph","created_at":"2026-05-18T00:35:41Z","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 aims to address two issues existing in the current speech enhancement methods: 1) the difficulty of phase estimations; 2) a single objective function cannot consider multiple metrics simultaneously. To solve the first problem, we propose a novel convolutional neural network (CNN) model for complex spectrogram enhancement, namely estimating clean real and imaginary (RI) spectrograms from noisy ones. The reconstructed RI spectrograms are directly used to synthesize enhanced speech waveforms. In addition, since log-power spectrogram (LPS) can be represented as a function of RI spectrog","authors_text":"Szu-Wei Fu, Ting-Yao Hu, Xugang Lu, Yu Tsao","cross_cats":["cs.LG","cs.SD"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-27T11:01:33Z","title":"Complex spectrogram enhancement by convolutional neural network with multi-metrics learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.08504","kind":"arxiv","version":2},"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":"sha256:936a81476cc06447d64bf88013c58fffa96b5191272facbb0d452f66949c1364","target":"record","created_at":"2026-05-18T00:35:41Z","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":"c3179546b9e8e1a020bc0c47169f9f63e22d648db1b8bb72f54b04eb7d3dba1c","cross_cats_sorted":["cs.LG","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-27T11:01:33Z","title_canon_sha256":"2bfa2aa3c6c0bec49f0e887012c5edef273dd879cac7dc2e5283c4bade5f4c6e"},"schema_version":"1.0","source":{"id":"1704.08504","kind":"arxiv","version":2}},"canonical_sha256":"caadbe86dba0d35a8efbd162450f64c58a320e73973c4109e6c6ce2dcab73742","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"caadbe86dba0d35a8efbd162450f64c58a320e73973c4109e6c6ce2dcab73742","first_computed_at":"2026-05-18T00:35:41.406770Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:35:41.406770Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e01E0KDAa+U9O9gH2+ujHnyScQUY/j7qyZkJJeQJkFUFy9G5o5ADReSCyxIs+QEwmo462FgimjYw7Ts0Cd/rAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:35:41.407479Z","signed_message":"canonical_sha256_bytes"},"source_id":"1704.08504","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:936a81476cc06447d64bf88013c58fffa96b5191272facbb0d452f66949c1364","sha256:61730f8b981ed55ac81de98421e32bdf366a04c84fa29bf06faef31199c5a729"],"state_sha256":"07d43dda49b9e138d16836af6ebc887f728e56cb305cc611fcd047bde8d92587"}