{"as_of":"2026-08-08T20:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fece524b1404ecff8b7bd4c8a5ead9c6da1575c73122b1a5bae6b8ef4cf97d16","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T00:27:32.622659Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T00:27:30.285078Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.01056","snapshot_observed_at":"2026-08-04T00:27:30.285078Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:30.285078Z"},"links":{"cited_paper":"/paper/2511.01056","citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:804d720693a14b1f2a8b7fd3057dbafe1bcefe1222368836c63e998b96e36d78","observation_id":"2033c47d-d8b4-407a-bf84-b43e0798d82e","resolution":{"observed_at":"2026-08-04T00:27:30.285078Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2511.01056/citation-record","integrity":"/paper/2511.01056/integrity","json":"/paper/2511.01056/citation-record.json","paper":"/paper/2511.01056"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.01056","snapshot_observed_at":"2026-08-04T00:27:30.285078Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:30.285078Z"},"links":{"cited_paper":"/paper/2511.01056","citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:804d720693a14b1f2a8b7fd3057dbafe1bcefe1222368836c63e998b96e36d78","observation_id":"2033c47d-d8b4-407a-bf84-b43e0798d82e","resolution":{"observed_at":"2026-08-04T00:27:30.285078Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:30.440254Z","title":"Overview The proposed whisper-to-speech (W2S) framework comprises three stages, as illustrated in Fig","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:30.440254Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:0f6ef6165d18897cb87e0d7047b925b9b1adc92208d497003a6acfa7b0fbafc2","observation_id":"6327563c-8ea8-4817-9ce9-72857de7159c","resolution":{"observed_at":"2026-08-04T00:27:30.440254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:30.539087Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:30.539087Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:fa1f316c89205e89131ab48241f3fb8dd3c9a667e9b371d1efbc917c1d493727","observation_id":"4bb93aa6-22ec-457e-958d-9c59077066d8","resolution":{"observed_at":"2026-08-04T00:27:30.539087Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:30.633764Z","title":"Objective evaluations show consistent gains over whispered inputs and performance approaching that of ground-truth recordings in terms of naturalness (DNSMOS 3.11, UTMOS 2.52vs","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:30.633764Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:802ed2cc763f65c55aa3deb7901a069e4f3af89079c29f1d012da7f590de6b91","observation_id":"83ea74e0-dfff-4670-89f7-f5e78a4d8f60","resolution":{"observed_at":"2026-08-04T00:27:30.633764Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.01342","last_updated":"2021-11-02T03:00:19Z","snapshot_observed_at":"2026-07-06T12:04:28.686580Z","submitted_at":"2021-11-02T03:00:19Z","title":"Attention-Guided Generative Adversarial Network for Whisper to Normal Speech Conversion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.01342","snapshot_observed_at":"2026-08-04T00:27:30.742369Z","title":"Attention-guided generative adversarial network for whisper to normal speech conversion,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:30.742369Z"},"links":{"cited_paper":"/paper/2111.01342","citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:c53eaf9a64b18aab7d9bd851e27159747a21497e2aa05c48cb775dcdf7409e02","observation_id":"93ae1124-b765-4d9a-b87f-b3b786023bad","resolution":{"observed_at":"2026-08-04T00:27:30.742369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:30.877727Z","title":"A novel attention-guided generative ad- versarial network for whisper-to-normal speech conversion,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:30.877727Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:5e6a57d9fee18c19752755d6641c984fe75ae5c23e564748cdb5c9c569a21089","observation_id":"030bb5cc-66fb-4cd9-bbca-eee124b96177","resolution":{"observed_at":"2026-08-04T00:27:30.877727Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.09347","last_updated":"2021-04-05T09:27:12Z","snapshot_observed_at":"2026-08-08T18:18:00.245784Z","submitted_at":"2020-04-20T14:47:46Z","title":"End-to-End Whisper to Natural Speech Conversion using Modified Transformer Network","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.09347","snapshot_observed_at":"2026-08-04T00:27:31.077349Z","title":"End-to-end whisper to natural speech conversion using modified transformer network,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:31.077349Z"},"links":{"cited_paper":"/paper/2004.09347","citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:1d9000b2bf78a52a67a74dc3775aeaf032894fedc1e10ff4db64e02550471d4b","observation_id":"1a6215b3-b46f-4579-b6ce-c1914bed3cea","resolution":{"observed_at":"2026-08-04T00:27:31.077349Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:31.209083Z","title":"Gener- ative adversarial networks for whispered to voiced speech con- version: a comparative study,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:31.209083Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:4e4d9944fc96362401d710e8551c29e703b60fb76e8e5bdd7fe138d3c8a639a7","observation_id":"2660c0f7-146d-46da-8c7c-55de5fa4a870","resolution":{"observed_at":"2026-08-04T00:27:31.209083Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:31.302379Z","title":"Maskcyclegan-based whisper to normal speech conversion,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:31.302379Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:6bc8cb8fd415de98098b3af9989225870950958112f5d3396237759484e441fe","observation_id":"ee10939d-fc61-4a92-bc9e-324173ed39a2","resolution":{"observed_at":"2026-08-04T00:27:31.302379Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:31.471258Z","title":"V ocoder-free non-parallel conversion of whispered speech with masked cycle-consistent generative adversarial net- works,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:31.471258Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:b4a70b514353fcd690934eae1516ca4644cac6a89cdf8b0807f6b134907127a2","observation_id":"e08590eb-faab-4165-879b-1d715e8a37cb","resolution":{"observed_at":"2026-08-04T00:27:31.471258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:31.592935Z","title":"Wesper: Zero-shot and realtime whisper to normal voice conversion for whisper-based speech interac- tions,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:31.592935Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:f14bb572b9583340a33a572fc183df63d000d00d958e1b1ff78649ab7b0a01c8","observation_id":"bd4b45c9-b9b1-4ea9-a473-2fb6394a360c","resolution":{"observed_at":"2026-08-04T00:27:31.592935Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:31.640744Z","title":"Distillw2n: A lightweight one-shot whisper to normal voice conversion model using distillation of self- supervised features,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:31.640744Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:81be682b27d6bbe91920fd88f00c0e79a78c5cdd8c106a706c715bc78c4e0cb1","observation_id":"01832f1e-6f80-4f34-b96a-89feb01029e7","resolution":{"observed_at":"2026-08-04T00:27:31.640744Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.11528","last_updated":"2024-08-21T11:09:48Z","snapshot_observed_at":"2026-08-07T12:38:41.628066Z","submitted_at":"2024-08-21T11:09:48Z","title":"Improvement Speaker Similarity for Zero-Shot Any-to-Any Voice Conversion of Whispered and Regular Speech","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.11528","snapshot_observed_at":"2026-08-04T00:27:31.662280Z","title":"Improvement speaker similarity for zero-shot any-to-any voice conversion of whis- pered and regular speech,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:31.662280Z"},"links":{"cited_paper":"/paper/2408.11528","citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:d9b41bed30c3cebffe00bc8feb45c29b49ee7691502117e280383163a94388e2","observation_id":"1a2a0a42-ddca-4696-8201-fbc699ef57aa","resolution":{"observed_at":"2026-08-04T00:27:31.662280Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:31.799075Z","title":"Whis- pered speech conversion based on the inversion of mel fre- quency cepstral coefficient features,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:31.799075Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:0bb08ec401a5d809b684acb2647c4298ca34d934a55e8ba7903fe75e6e45e893","observation_id":"894eef0e-9f7d-48dd-887c-61da2d95b4e9","resolution":{"observed_at":"2026-08-04T00:27:31.799075Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:31.932344Z","title":"Glottal flow synthesis for whisper-to-speech conversion,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:31.932344Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:2fcd606c46cc6351bc659735cb988ef4bae83529d37840c6c0b36d5ba1dfccc7","observation_id":"31dae4b7-00d6-4f15-b7a9-e23d9e3303e6","resolution":{"observed_at":"2026-08-04T00:27:31.932344Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:32.088017Z","title":"Robust speech recognition via large-scale weak supervision,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:32.088017Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:1747309b4014f3516c447f65871f329bf3cd5d434fcdc53b9f7abf62b23f9f38","observation_id":"27428f30-a187-4aef-8e21-e3c211174b1b","resolution":{"observed_at":"2026-08-04T00:27:32.088017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:32.208797Z","title":"Aishell6-whisper: A chinese mandarin audio-visual whisper speech dataset with speech recognition baselines,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:32.208797Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:0cf7d001fdb9f706b84258e9709cc75295f3e0376d470b85885b36fe79e3f569","observation_id":"467a1e4a-1c9b-4d7a-86b9-ec7f070fe0ce","resolution":{"observed_at":"2026-08-04T00:27:32.208797Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:32.325364Z","title":"Soft-dtw: a differentiable loss function for time-series,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:32.325364Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:e4d0e499e9df61376827f04a10f8281086460828636be19ebd6f6ce2eeca181b","observation_id":"1aa43ace-e3cb-442d-840a-997ac9e62c34","resolution":{"observed_at":"2026-08-04T00:27:32.325364Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.04558","last_updated":"2022-08-08T01:53:05Z","snapshot_observed_at":"2026-08-06T18:05:37.673476Z","submitted_at":"2020-06-08T13:05:40Z","title":"FastSpeech 2: Fast and High-Quality End-to-End Text to Speech","version":8},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.04558","snapshot_observed_at":"2026-08-04T00:27:32.435469Z","title":"Fastspeech 2: Fast and high-quality end-to- end text to speech,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:32.435469Z"},"links":{"cited_paper":"/paper/2006.04558","citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:1c1006ed1e85c3e877a1b21de4b577cd6cdcd14cea0fe2e9a938a067c9dfc132","observation_id":"7dac97be-17ba-447e-ad96-257d4e781f18","resolution":{"observed_at":"2026-08-04T00:27:32.435469Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:32.459345Z","title":"Wespeaker: A research and production oriented speaker embedding learning toolkit,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:32.459345Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:76b0a3e1838158d8f821d74cf140c63824208562b967f0dfe99c5af59538b54f","observation_id":"6d8a2234-0ca5-4a03-b47e-b1c4c88de3c2","resolution":{"observed_at":"2026-08-04T00:27:32.459345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.11510","last_updated":"2024-07-16T08:49:30Z","snapshot_observed_at":"2026-07-06T18:47:00.524107Z","submitted_at":"2024-07-16T08:49:30Z","title":"VoxBlink2: A 100K+ Speaker Recognition Corpus and the Open-Set Speaker-Identification Benchmark","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.11510","snapshot_observed_at":"2026-08-04T00:27:32.487566Z","title":"V oxblink2: A 100k+ speaker recog- nition corpus and the open-set speaker-identification bench- mark,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:32.487566Z"},"links":{"cited_paper":"/paper/2407.11510","citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:3d3ea5b84ba422497a5d80bd50c29c912fee957f3440b428f80facae0c1885a5","observation_id":"4ea14fc2-563a-4b30-9675-108021d84dff","resolution":{"observed_at":"2026-08-04T00:27:32.487566Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.05622","last_updated":"2018-06-27T01:49:17Z","snapshot_observed_at":"2026-08-08T04:36:13.309903Z","submitted_at":"2018-06-14T15:59:12Z","title":"VoxCeleb2: Deep Speaker Recognition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.05622","snapshot_observed_at":"2026-08-04T00:27:32.599880Z","title":"V oxceleb2: Deep speaker recognition,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:32.599880Z"},"links":{"cited_paper":"/paper/1806.05622","citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:8dc82f11b70cb152e71c22372ee7e5c6c0b9460aad6a71bc0b3d66269b93aa56","observation_id":"3945a79a-ecfe-4eac-8e1c-4e45dd8250e5","resolution":{"observed_at":"2026-08-04T00:27:32.599880Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:32.617233Z","title":"Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:32.617233Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:3342d15056f4c3fad24872623901b3807e9b0eff32552479254e2820d518634a","observation_id":"de3b0585-e9fd-4f91-b6fe-3b758095457c","resolution":{"observed_at":"2026-08-04T00:27:32.617233Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T00:27:32.620011Z","title":"Dnsmos: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:32.620011Z"},"links":{"citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:273caad3ed9eb0be96260b4fee4076046e16df80b801d0c2e217ee072afee93b","observation_id":"5cbee1b4-df98-485e-891e-deffc5ba766a","resolution":{"observed_at":"2026-08-04T00:27:32.620011Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.02152","last_updated":"2022-06-29T13:42:05Z","snapshot_observed_at":"2026-08-04T06:18:23.412967Z","submitted_at":"2022-04-05T12:23:51Z","title":"UTMOS: UTokyo-SaruLab System for VoiceMOS Challenge 2022","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.02152","snapshot_observed_at":"2026-08-04T00:27:32.622659Z","title":"Utmos: Utokyo-sarulab system for voicemos challenge 2022,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-04T00:27:32.622659Z"},"links":{"cited_paper":"/paper/2204.02152","citing_paper":"/paper/2511.01056"},"observation_digest":"sha256:5394fdf445de6cc01f7dcacb6eeca7c1c08f0de9e1de0f5e6e61af14ea88a91e","observation_id":"1a38ff9c-55ca-4e97-9ee8-0db8bbd969e2","resolution":{"observed_at":"2026-08-04T00:27:32.622659Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2511.01056","last_updated":"2026-07-20T02:49:17Z","latest_version":3,"primary_category":"eess.AS","snapshot_observed_at":"2026-08-06T19:49:52.311111Z","submitted_at":"2025-11-02T19:18:38Z","title":"WhisperVC: Decoupled Cross-Domain Alignment and Speech Generation for Low-Resource Whisper-to-Normal Conversion"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":25,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":25},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2511.01056."}