{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:S73GURWUZ25BN4GL2B4UGQLITT","short_pith_number":"pith:S73GURWU","canonical_record":{"source":{"id":"2202.07816","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-02-16T01:42:32Z","cross_cats_sorted":["cs.CL","cs.SD"],"title_canon_sha256":"cb920af3bb8c8208d2c130d1c013746063f40657deb9624d82f5d82cc853c381","abstract_canon_sha256":"3a61c2e4bfc08617bd00f7ead33ca6dca87093fd4c9edc8abb27d52c9651e9c8"},"schema_version":"1.0"},"canonical_sha256":"97f66a46d4ceba16f0cbd0794341689cd8c0e6f2889a0df39f4c0fceba50bb3a","source":{"kind":"arxiv","id":"2202.07816","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.07816","created_at":"2026-07-05T03:57:33Z"},{"alias_kind":"arxiv_version","alias_value":"2202.07816v1","created_at":"2026-07-05T03:57:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.07816","created_at":"2026-07-05T03:57:33Z"},{"alias_kind":"pith_short_12","alias_value":"S73GURWUZ25B","created_at":"2026-07-05T03:57:33Z"},{"alias_kind":"pith_short_16","alias_value":"S73GURWUZ25BN4GL","created_at":"2026-07-05T03:57:33Z"},{"alias_kind":"pith_short_8","alias_value":"S73GURWU","created_at":"2026-07-05T03:57:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:S73GURWUZ25BN4GL2B4UGQLITT","target":"record","payload":{"canonical_record":{"source":{"id":"2202.07816","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-02-16T01:42:32Z","cross_cats_sorted":["cs.CL","cs.SD"],"title_canon_sha256":"cb920af3bb8c8208d2c130d1c013746063f40657deb9624d82f5d82cc853c381","abstract_canon_sha256":"3a61c2e4bfc08617bd00f7ead33ca6dca87093fd4c9edc8abb27d52c9651e9c8"},"schema_version":"1.0"},"canonical_sha256":"97f66a46d4ceba16f0cbd0794341689cd8c0e6f2889a0df39f4c0fceba50bb3a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:57:33.932405Z","signature_b64":"uuX70o4zVBxWThnOL8CwP8Q4yTp0HEU7GRWhPTwAPmReIWgZZT7mILFz+20gVfLHoEO92ZoMboRMGHbsIWGdDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"97f66a46d4ceba16f0cbd0794341689cd8c0e6f2889a0df39f4c0fceba50bb3a","last_reissued_at":"2026-07-05T03:57:33.932001Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:57:33.932001Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2202.07816","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:57:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LM1L/JfWZ/szuXxLjD+cXgYJHDvNGPm2NiNHRwUjgD31tcgctaXfto/8yh7XSGxbyHDbXAyOvNt5eIKhTcwlCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T18:40:26.346662Z"},"content_sha256":"ea6dde9d9a144e70bdf426d18052a0211766e78ac88db0a5f29b5cf57a4931fc","schema_version":"1.0","event_id":"sha256:ea6dde9d9a144e70bdf426d18052a0211766e78ac88db0a5f29b5cf57a4931fc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:S73GURWUZ25BN4GL2B4UGQLITT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ProsoSpeech: Enhancing Prosody With Quantized Vector Pre-training in Text-to-Speech","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.SD"],"primary_cat":"eess.AS","authors_text":"Ming Lei, Qian Chen, Shiliang Zhang, Yi Ren, Zhijie Yan, Zhiying Huang, Zhou Zhao","submitted_at":"2022-02-16T01:42:32Z","abstract_excerpt":"Expressive text-to-speech (TTS) has become a hot research topic recently, mainly focusing on modeling prosody in speech. Prosody modeling has several challenges: 1) the extracted pitch used in previous prosody modeling works have inevitable errors, which hurts the prosody modeling; 2) different attributes of prosody (e.g., pitch, duration and energy) are dependent on each other and produce the natural prosody together; and 3) due to high variability of prosody and the limited amount of high-quality data for TTS training, the distribution of prosody cannot be fully shaped. To tackle these issue"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.07816","kind":"arxiv","version":1},"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/2202.07816/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":"2026-07-05T03:57:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fdWVLFTOLy9QNCEPfT9lDoG0HWcuZGSlFxQ7FI6l47PwSquYEq7rBo+nSJkDCuHF6GpR/IQoUillLlLU2Q2GBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T18:40:26.347038Z"},"content_sha256":"7a58cd05f9ac12eab3f96014157892ff0e1069b62049fd38f03d9e90b1b32556","schema_version":"1.0","event_id":"sha256:7a58cd05f9ac12eab3f96014157892ff0e1069b62049fd38f03d9e90b1b32556"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S73GURWUZ25BN4GL2B4UGQLITT/bundle.json","state_url":"https://pith.science/pith/S73GURWUZ25BN4GL2B4UGQLITT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S73GURWUZ25BN4GL2B4UGQLITT/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":"2026-07-12T18:40:26Z","links":{"resolver":"https://pith.science/pith/S73GURWUZ25BN4GL2B4UGQLITT","bundle":"https://pith.science/pith/S73GURWUZ25BN4GL2B4UGQLITT/bundle.json","state":"https://pith.science/pith/S73GURWUZ25BN4GL2B4UGQLITT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S73GURWUZ25BN4GL2B4UGQLITT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:S73GURWUZ25BN4GL2B4UGQLITT","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":"3a61c2e4bfc08617bd00f7ead33ca6dca87093fd4c9edc8abb27d52c9651e9c8","cross_cats_sorted":["cs.CL","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-02-16T01:42:32Z","title_canon_sha256":"cb920af3bb8c8208d2c130d1c013746063f40657deb9624d82f5d82cc853c381"},"schema_version":"1.0","source":{"id":"2202.07816","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.07816","created_at":"2026-07-05T03:57:33Z"},{"alias_kind":"arxiv_version","alias_value":"2202.07816v1","created_at":"2026-07-05T03:57:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.07816","created_at":"2026-07-05T03:57:33Z"},{"alias_kind":"pith_short_12","alias_value":"S73GURWUZ25B","created_at":"2026-07-05T03:57:33Z"},{"alias_kind":"pith_short_16","alias_value":"S73GURWUZ25BN4GL","created_at":"2026-07-05T03:57:33Z"},{"alias_kind":"pith_short_8","alias_value":"S73GURWU","created_at":"2026-07-05T03:57:33Z"}],"graph_snapshots":[{"event_id":"sha256:7a58cd05f9ac12eab3f96014157892ff0e1069b62049fd38f03d9e90b1b32556","target":"graph","created_at":"2026-07-05T03:57:33Z","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/2202.07816/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Expressive text-to-speech (TTS) has become a hot research topic recently, mainly focusing on modeling prosody in speech. Prosody modeling has several challenges: 1) the extracted pitch used in previous prosody modeling works have inevitable errors, which hurts the prosody modeling; 2) different attributes of prosody (e.g., pitch, duration and energy) are dependent on each other and produce the natural prosody together; and 3) due to high variability of prosody and the limited amount of high-quality data for TTS training, the distribution of prosody cannot be fully shaped. To tackle these issue","authors_text":"Ming Lei, Qian Chen, Shiliang Zhang, Yi Ren, Zhijie Yan, Zhiying Huang, Zhou Zhao","cross_cats":["cs.CL","cs.SD"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-02-16T01:42:32Z","title":"ProsoSpeech: Enhancing Prosody With Quantized Vector Pre-training in Text-to-Speech"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.07816","kind":"arxiv","version":1},"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:ea6dde9d9a144e70bdf426d18052a0211766e78ac88db0a5f29b5cf57a4931fc","target":"record","created_at":"2026-07-05T03:57:33Z","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":"3a61c2e4bfc08617bd00f7ead33ca6dca87093fd4c9edc8abb27d52c9651e9c8","cross_cats_sorted":["cs.CL","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-02-16T01:42:32Z","title_canon_sha256":"cb920af3bb8c8208d2c130d1c013746063f40657deb9624d82f5d82cc853c381"},"schema_version":"1.0","source":{"id":"2202.07816","kind":"arxiv","version":1}},"canonical_sha256":"97f66a46d4ceba16f0cbd0794341689cd8c0e6f2889a0df39f4c0fceba50bb3a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97f66a46d4ceba16f0cbd0794341689cd8c0e6f2889a0df39f4c0fceba50bb3a","first_computed_at":"2026-07-05T03:57:33.932001Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:57:33.932001Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uuX70o4zVBxWThnOL8CwP8Q4yTp0HEU7GRWhPTwAPmReIWgZZT7mILFz+20gVfLHoEO92ZoMboRMGHbsIWGdDg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:57:33.932405Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.07816","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ea6dde9d9a144e70bdf426d18052a0211766e78ac88db0a5f29b5cf57a4931fc","sha256:7a58cd05f9ac12eab3f96014157892ff0e1069b62049fd38f03d9e90b1b32556"],"state_sha256":"db376acd81fde55df27138e52e3bf2b1f9d6074673acb4a7935337fcfc24d688"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D40QjSmWKBB9fmcsCFVdn4Nfpr6/vCpHkjFy26pGE+VVtovsxEQPZ1jPmxiMX6EFu66SsAnjWULmyjQEER6MCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-12T18:40:26.349485Z","bundle_sha256":"3681b057b7c7f0c79b7748c40d56d3e759f803026c7741e03da4155f4d4e5481"}}