{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:Z3WL6HXBINKSEN6DWRXHJNDGMI","short_pith_number":"pith:Z3WL6HXB","canonical_record":{"source":{"id":"1711.11293","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-30T09:57:19Z","cross_cats_sorted":["cs.SD","eess.AS"],"title_canon_sha256":"4974ec8158aa5c9c07721202f9ba656e326aa17927caf1b33ff4c52842c42495","abstract_canon_sha256":"12dcb00412d41e8c8b0e32977923f03a27222a1fd700cae14a96b4f35b301e12"},"schema_version":"1.0"},"canonical_sha256":"ceecbf1ee143552237c3b46e74b4666228bc4fd49c243c84941b76a26b1680ba","source":{"kind":"arxiv","id":"1711.11293","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.11293","created_at":"2026-05-18T00:27:35Z"},{"alias_kind":"arxiv_version","alias_value":"1711.11293v2","created_at":"2026-05-18T00:27:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.11293","created_at":"2026-05-18T00:27:35Z"},{"alias_kind":"pith_short_12","alias_value":"Z3WL6HXBINKS","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"Z3WL6HXBINKSEN6D","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"Z3WL6HXB","created_at":"2026-05-18T12:31:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:Z3WL6HXBINKSEN6DWRXHJNDGMI","target":"record","payload":{"canonical_record":{"source":{"id":"1711.11293","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-30T09:57:19Z","cross_cats_sorted":["cs.SD","eess.AS"],"title_canon_sha256":"4974ec8158aa5c9c07721202f9ba656e326aa17927caf1b33ff4c52842c42495","abstract_canon_sha256":"12dcb00412d41e8c8b0e32977923f03a27222a1fd700cae14a96b4f35b301e12"},"schema_version":"1.0"},"canonical_sha256":"ceecbf1ee143552237c3b46e74b4666228bc4fd49c243c84941b76a26b1680ba","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:27:35.648815Z","signature_b64":"kc6p2RBVx412z+0WoVjJtt4lspfQ9kE7CWvHNoxUgzOD9JJV9ogtf6reAQLbmaa/BxQHqVha4pzsxsl5++a5AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ceecbf1ee143552237c3b46e74b4666228bc4fd49c243c84941b76a26b1680ba","last_reissued_at":"2026-05-18T00:27:35.648281Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:27:35.648281Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.11293","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":"2026-05-18T00:27:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FcZoLg6Wo1cgLV9rjyQTgs1BVpAdmiULq1cV7+GmACCItcN7K5elAokoULA7LEJsASTiG/oW6oLbW5wMDcLNCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T12:27:11.985968Z"},"content_sha256":"10d5f2e2418175aea3444937bc966296ba94fc1f2586b2e55c52533dc6ec3f57","schema_version":"1.0","event_id":"sha256:10d5f2e2418175aea3444937bc966296ba94fc1f2586b2e55c52533dc6ec3f57"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:Z3WL6HXBINKSEN6DWRXHJNDGMI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Parallel-Data-Free Voice Conversion Using Cycle-Consistent Adversarial Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SD","eess.AS"],"primary_cat":"stat.ML","authors_text":"Hirokazu Kameoka, Takuhiro Kaneko","submitted_at":"2017-11-30T09:57:19Z","abstract_excerpt":"We propose a parallel-data-free voice-conversion (VC) method that can learn a mapping from source to target speech without relying on parallel data. The proposed method is general purpose, high quality, and parallel-data free and works without any extra data, modules, or alignment procedure. It also avoids over-smoothing, which occurs in many conventional statistical model-based VC methods. Our method, called CycleGAN-VC, uses a cycle-consistent adversarial network (CycleGAN) with gated convolutional neural networks (CNNs) and an identity-mapping loss. A CycleGAN learns forward and inverse map"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.11293","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":""},"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":"2026-05-18T00:27:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BzTSfLeVmDugjYHWG2BGsQGWu8vWYeuQav2E8kExeL/nXBP0qGjMVznngZDhOPCdsKs5j3klm5M26jqiIOSwBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T12:27:11.986629Z"},"content_sha256":"afeb9d56acf08d8891e57b08709a2c22246a60c4793d5fe74f9d90b8cd6a6b3f","schema_version":"1.0","event_id":"sha256:afeb9d56acf08d8891e57b08709a2c22246a60c4793d5fe74f9d90b8cd6a6b3f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Z3WL6HXBINKSEN6DWRXHJNDGMI/bundle.json","state_url":"https://pith.science/pith/Z3WL6HXBINKSEN6DWRXHJNDGMI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Z3WL6HXBINKSEN6DWRXHJNDGMI/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":"2026-05-27T12:27:11Z","links":{"resolver":"https://pith.science/pith/Z3WL6HXBINKSEN6DWRXHJNDGMI","bundle":"https://pith.science/pith/Z3WL6HXBINKSEN6DWRXHJNDGMI/bundle.json","state":"https://pith.science/pith/Z3WL6HXBINKSEN6DWRXHJNDGMI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Z3WL6HXBINKSEN6DWRXHJNDGMI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:Z3WL6HXBINKSEN6DWRXHJNDGMI","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":"12dcb00412d41e8c8b0e32977923f03a27222a1fd700cae14a96b4f35b301e12","cross_cats_sorted":["cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-30T09:57:19Z","title_canon_sha256":"4974ec8158aa5c9c07721202f9ba656e326aa17927caf1b33ff4c52842c42495"},"schema_version":"1.0","source":{"id":"1711.11293","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.11293","created_at":"2026-05-18T00:27:35Z"},{"alias_kind":"arxiv_version","alias_value":"1711.11293v2","created_at":"2026-05-18T00:27:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.11293","created_at":"2026-05-18T00:27:35Z"},{"alias_kind":"pith_short_12","alias_value":"Z3WL6HXBINKS","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"Z3WL6HXBINKSEN6D","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"Z3WL6HXB","created_at":"2026-05-18T12:31:59Z"}],"graph_snapshots":[{"event_id":"sha256:afeb9d56acf08d8891e57b08709a2c22246a60c4793d5fe74f9d90b8cd6a6b3f","target":"graph","created_at":"2026-05-18T00:27:35Z","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":"We propose a parallel-data-free voice-conversion (VC) method that can learn a mapping from source to target speech without relying on parallel data. The proposed method is general purpose, high quality, and parallel-data free and works without any extra data, modules, or alignment procedure. It also avoids over-smoothing, which occurs in many conventional statistical model-based VC methods. Our method, called CycleGAN-VC, uses a cycle-consistent adversarial network (CycleGAN) with gated convolutional neural networks (CNNs) and an identity-mapping loss. A CycleGAN learns forward and inverse map","authors_text":"Hirokazu Kameoka, Takuhiro Kaneko","cross_cats":["cs.SD","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-30T09:57:19Z","title":"Parallel-Data-Free Voice Conversion Using Cycle-Consistent Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.11293","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":"sha256:10d5f2e2418175aea3444937bc966296ba94fc1f2586b2e55c52533dc6ec3f57","target":"record","created_at":"2026-05-18T00:27:35Z","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":"12dcb00412d41e8c8b0e32977923f03a27222a1fd700cae14a96b4f35b301e12","cross_cats_sorted":["cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-30T09:57:19Z","title_canon_sha256":"4974ec8158aa5c9c07721202f9ba656e326aa17927caf1b33ff4c52842c42495"},"schema_version":"1.0","source":{"id":"1711.11293","kind":"arxiv","version":2}},"canonical_sha256":"ceecbf1ee143552237c3b46e74b4666228bc4fd49c243c84941b76a26b1680ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ceecbf1ee143552237c3b46e74b4666228bc4fd49c243c84941b76a26b1680ba","first_computed_at":"2026-05-18T00:27:35.648281Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:27:35.648281Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kc6p2RBVx412z+0WoVjJtt4lspfQ9kE7CWvHNoxUgzOD9JJV9ogtf6reAQLbmaa/BxQHqVha4pzsxsl5++a5AA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:27:35.648815Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.11293","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:10d5f2e2418175aea3444937bc966296ba94fc1f2586b2e55c52533dc6ec3f57","sha256:afeb9d56acf08d8891e57b08709a2c22246a60c4793d5fe74f9d90b8cd6a6b3f"],"state_sha256":"e9beffe39300928b7554d73ec2532ae2856043cd737188fbc47a8e0bdcc3d4fd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h6JTkvCtxYx6gySxCbt8HhxyIwtT6BAnyzzuXIQVVTGR3mDV3dQpD71J6XoVoge7MNffo7znrHSYbe7O/W3XAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T12:27:11.990252Z","bundle_sha256":"f220b707329f2130c2945517a4fdf819c3b5b028d93bb63b5bcb62ca53e8bd92"}}