{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:SOE42A6ZO2OUSQ6IYNXMRXADDC","short_pith_number":"pith:SOE42A6Z","canonical_record":{"source":{"id":"2206.04658","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2022-06-09T17:56:10Z","cross_cats_sorted":["cs.CL","cs.LG","eess.AS"],"title_canon_sha256":"6be55ec8743851629f5a8231a019aacc5e487bf5697ce13836990e261c9170c7","abstract_canon_sha256":"230212724a3da2e9f1cff6a0939f133e735444410044161d995e80e12786693a"},"schema_version":"1.0"},"canonical_sha256":"9389cd03d9769d4943c8c36ec8dc03189162cd574f9afe16762dbac39141b1c0","source":{"kind":"arxiv","id":"2206.04658","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.04658","created_at":"2026-07-05T05:42:25Z"},{"alias_kind":"arxiv_version","alias_value":"2206.04658v2","created_at":"2026-07-05T05:42:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.04658","created_at":"2026-07-05T05:42:25Z"},{"alias_kind":"pith_short_12","alias_value":"SOE42A6ZO2OU","created_at":"2026-07-05T05:42:25Z"},{"alias_kind":"pith_short_16","alias_value":"SOE42A6ZO2OUSQ6I","created_at":"2026-07-05T05:42:25Z"},{"alias_kind":"pith_short_8","alias_value":"SOE42A6Z","created_at":"2026-07-05T05:42:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:SOE42A6ZO2OUSQ6IYNXMRXADDC","target":"record","payload":{"canonical_record":{"source":{"id":"2206.04658","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2022-06-09T17:56:10Z","cross_cats_sorted":["cs.CL","cs.LG","eess.AS"],"title_canon_sha256":"6be55ec8743851629f5a8231a019aacc5e487bf5697ce13836990e261c9170c7","abstract_canon_sha256":"230212724a3da2e9f1cff6a0939f133e735444410044161d995e80e12786693a"},"schema_version":"1.0"},"canonical_sha256":"9389cd03d9769d4943c8c36ec8dc03189162cd574f9afe16762dbac39141b1c0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:42:25.604933Z","signature_b64":"3X1/TXXZevcXT0QjD7jZhf76z1mQ2FeXOVWnXP13lyIEzYbEA9agUHJlm4+3Ynk77KPzq+qaxUKTL1lM1aNhBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9389cd03d9769d4943c8c36ec8dc03189162cd574f9afe16762dbac39141b1c0","last_reissued_at":"2026-07-05T05:42:25.604493Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:42:25.604493Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2206.04658","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:42:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v/j3WiECj/y9LgLXZnH6c8aKT4kune4ALpHyJk7uTcnMpLKpXcCrp6Ik2Uyz14IrC78HVt0ADTSmEDGPSKPiCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T08:15:42.003577Z"},"content_sha256":"de966149b75427fd0e5f21ecfe26bca5348abac1d82b3210ab71e867dc236b15","schema_version":"1.0","event_id":"sha256:de966149b75427fd0e5f21ecfe26bca5348abac1d82b3210ab71e867dc236b15"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:SOE42A6ZO2OUSQ6IYNXMRXADDC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"BigVGAN: A Universal Neural Vocoder with Large-Scale Training","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.LG","eess.AS"],"primary_cat":"cs.SD","authors_text":"Boris Ginsburg, Bryan Catanzaro, Sang-gil Lee, Sungroh Yoon, Wei Ping","submitted_at":"2022-06-09T17:56:10Z","abstract_excerpt":"Despite recent progress in generative adversarial network (GAN)-based vocoders, where the model generates raw waveform conditioned on acoustic features, it is challenging to synthesize high-fidelity audio for numerous speakers across various recording environments. In this work, we present BigVGAN, a universal vocoder that generalizes well for various out-of-distribution scenarios without fine-tuning. We introduce periodic activation function and anti-aliased representation into the GAN generator, which brings the desired inductive bias for audio synthesis and significantly improves audio qual"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.04658","kind":"arxiv","version":2},"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/2206.04658/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":"2026-07-05T05:42:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z+gnrARf5+JK1zUGn0cIkjgsAEdNrSKfhpARp/f+i89TgnJV76Rc4GbT4Zk41uB9jDHqgLJ3wLHfYvhFN6QJCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T08:15:42.003958Z"},"content_sha256":"866ce6a39d754d01b8454071924b96906b863336dbda5aeae9b32b91b6159341","schema_version":"1.0","event_id":"sha256:866ce6a39d754d01b8454071924b96906b863336dbda5aeae9b32b91b6159341"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SOE42A6ZO2OUSQ6IYNXMRXADDC/bundle.json","state_url":"https://pith.science/pith/SOE42A6ZO2OUSQ6IYNXMRXADDC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SOE42A6ZO2OUSQ6IYNXMRXADDC/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":"2026-07-11T08:15:42Z","links":{"resolver":"https://pith.science/pith/SOE42A6ZO2OUSQ6IYNXMRXADDC","bundle":"https://pith.science/pith/SOE42A6ZO2OUSQ6IYNXMRXADDC/bundle.json","state":"https://pith.science/pith/SOE42A6ZO2OUSQ6IYNXMRXADDC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SOE42A6ZO2OUSQ6IYNXMRXADDC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:SOE42A6ZO2OUSQ6IYNXMRXADDC","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":"230212724a3da2e9f1cff6a0939f133e735444410044161d995e80e12786693a","cross_cats_sorted":["cs.CL","cs.LG","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2022-06-09T17:56:10Z","title_canon_sha256":"6be55ec8743851629f5a8231a019aacc5e487bf5697ce13836990e261c9170c7"},"schema_version":"1.0","source":{"id":"2206.04658","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.04658","created_at":"2026-07-05T05:42:25Z"},{"alias_kind":"arxiv_version","alias_value":"2206.04658v2","created_at":"2026-07-05T05:42:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.04658","created_at":"2026-07-05T05:42:25Z"},{"alias_kind":"pith_short_12","alias_value":"SOE42A6ZO2OU","created_at":"2026-07-05T05:42:25Z"},{"alias_kind":"pith_short_16","alias_value":"SOE42A6ZO2OUSQ6I","created_at":"2026-07-05T05:42:25Z"},{"alias_kind":"pith_short_8","alias_value":"SOE42A6Z","created_at":"2026-07-05T05:42:25Z"}],"graph_snapshots":[{"event_id":"sha256:866ce6a39d754d01b8454071924b96906b863336dbda5aeae9b32b91b6159341","target":"graph","created_at":"2026-07-05T05:42:25Z","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/2206.04658/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite recent progress in generative adversarial network (GAN)-based vocoders, where the model generates raw waveform conditioned on acoustic features, it is challenging to synthesize high-fidelity audio for numerous speakers across various recording environments. In this work, we present BigVGAN, a universal vocoder that generalizes well for various out-of-distribution scenarios without fine-tuning. We introduce periodic activation function and anti-aliased representation into the GAN generator, which brings the desired inductive bias for audio synthesis and significantly improves audio qual","authors_text":"Boris Ginsburg, Bryan Catanzaro, Sang-gil Lee, Sungroh Yoon, Wei Ping","cross_cats":["cs.CL","cs.LG","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2022-06-09T17:56:10Z","title":"BigVGAN: A Universal Neural Vocoder with Large-Scale Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.04658","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:de966149b75427fd0e5f21ecfe26bca5348abac1d82b3210ab71e867dc236b15","target":"record","created_at":"2026-07-05T05:42:25Z","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":"230212724a3da2e9f1cff6a0939f133e735444410044161d995e80e12786693a","cross_cats_sorted":["cs.CL","cs.LG","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2022-06-09T17:56:10Z","title_canon_sha256":"6be55ec8743851629f5a8231a019aacc5e487bf5697ce13836990e261c9170c7"},"schema_version":"1.0","source":{"id":"2206.04658","kind":"arxiv","version":2}},"canonical_sha256":"9389cd03d9769d4943c8c36ec8dc03189162cd574f9afe16762dbac39141b1c0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9389cd03d9769d4943c8c36ec8dc03189162cd574f9afe16762dbac39141b1c0","first_computed_at":"2026-07-05T05:42:25.604493Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:42:25.604493Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3X1/TXXZevcXT0QjD7jZhf76z1mQ2FeXOVWnXP13lyIEzYbEA9agUHJlm4+3Ynk77KPzq+qaxUKTL1lM1aNhBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:42:25.604933Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.04658","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:de966149b75427fd0e5f21ecfe26bca5348abac1d82b3210ab71e867dc236b15","sha256:866ce6a39d754d01b8454071924b96906b863336dbda5aeae9b32b91b6159341"],"state_sha256":"a02faf47a183883782e304cfbda80c95b63e4ec01d540a758a489faaf6a493e6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JkLUOQKPCzKnV+6Oi79vWeurDoFC7p6zRkIDFtA6XDVNMMuj2H5e5ntbEzYgf7wWRD5s6MNZCTet2w6vd6bMBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T08:15:42.006125Z","bundle_sha256":"dfaacec505f5a3418c00deaea15a3c0ddc228992641f4d5aab5c5d23fb22060b"}}