{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:XHVOYJMLEJESIDS4CBDKWVZDCX","short_pith_number":"pith:XHVOYJML","canonical_record":{"source":{"id":"2211.09536","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-11-17T13:59:34Z","cross_cats_sorted":["cs.LG","cs.SD","eess.AS"],"title_canon_sha256":"64c0370b218e19da60f400314c9eed7d684fe8a89586ff6c5abf69ec7cceb89e","abstract_canon_sha256":"211cdbdd5b541af64a0262d9458b4d2e21b3f7b9ea519521fbd22718f12b129f"},"schema_version":"1.0"},"canonical_sha256":"b9eaec258b2249240e5c1046ab572315d13af6fa1f1d95443d95edc503606dc3","source":{"kind":"arxiv","id":"2211.09536","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.09536","created_at":"2026-07-05T05:42:49Z"},{"alias_kind":"arxiv_version","alias_value":"2211.09536v3","created_at":"2026-07-05T05:42:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.09536","created_at":"2026-07-05T05:42:49Z"},{"alias_kind":"pith_short_12","alias_value":"XHVOYJMLEJES","created_at":"2026-07-05T05:42:49Z"},{"alias_kind":"pith_short_16","alias_value":"XHVOYJMLEJESIDS4","created_at":"2026-07-05T05:42:49Z"},{"alias_kind":"pith_short_8","alias_value":"XHVOYJML","created_at":"2026-07-05T05:42:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:XHVOYJMLEJESIDS4CBDKWVZDCX","target":"record","payload":{"canonical_record":{"source":{"id":"2211.09536","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-11-17T13:59:34Z","cross_cats_sorted":["cs.LG","cs.SD","eess.AS"],"title_canon_sha256":"64c0370b218e19da60f400314c9eed7d684fe8a89586ff6c5abf69ec7cceb89e","abstract_canon_sha256":"211cdbdd5b541af64a0262d9458b4d2e21b3f7b9ea519521fbd22718f12b129f"},"schema_version":"1.0"},"canonical_sha256":"b9eaec258b2249240e5c1046ab572315d13af6fa1f1d95443d95edc503606dc3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:42:49.995876Z","signature_b64":"8zcViS3Mdu3kOf3fCT2u8VgK5D6/DV14lQJJm+OO5nzuiWBfmejWH+yH7A0DBVDb95fzNNjmMmQemWO62APvBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b9eaec258b2249240e5c1046ab572315d13af6fa1f1d95443d95edc503606dc3","last_reissued_at":"2026-07-05T05:42:49.995456Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:42:49.995456Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.09536","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:42:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qaZkRyPGTav/xbhNNtsVOaGKzQZ9M8uyAMAdR/RcTLQXVBmHPZN7ywAKQvmoD3fMy5YlmC+VXE6S497nyP4lDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T19:13:36.403578Z"},"content_sha256":"028fa75f1f042fd142a2b59a22f8836816063f17b9e18f58f89f3df0629ad0a8","schema_version":"1.0","event_id":"sha256:028fa75f1f042fd142a2b59a22f8836816063f17b9e18f58f89f3df0629ad0a8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:XHVOYJMLEJESIDS4CBDKWVZDCX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Building Text-To-Speech Systems for the Next Billion Users","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SD","eess.AS"],"primary_cat":"cs.CL","authors_text":"Gokul Karthik Kumar, Karthik Nandakumar, Mitesh M. Khapra, Pratyush Kumar, Praveen S V","submitted_at":"2022-11-17T13:59:34Z","abstract_excerpt":"Deep learning based text-to-speech (TTS) systems have been evolving rapidly with advances in model architectures, training methodologies, and generalization across speakers and languages. However, these advances have not been thoroughly investigated for Indian language speech synthesis. Such investigation is computationally expensive given the number and diversity of Indian languages, relatively lower resource availability, and the diverse set of advances in neural TTS that remain untested. In this paper, we evaluate the choice of acoustic models, vocoders, supplementary loss functions, traini"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.09536","kind":"arxiv","version":3},"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/2211.09536/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":"2026-07-05T05:42:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Nne+VCBcSbmZxHq3FZzEboPOQuw37vtRAuUUgx8ll9gspsZ6iLV5UQOi0+frHfuqZfnlSjJ9GIuS48EMsoeFBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T19:13:36.404187Z"},"content_sha256":"02a2df7585d325e2e80191c8c1d189121385899215dfcccde1229550f46540e7","schema_version":"1.0","event_id":"sha256:02a2df7585d325e2e80191c8c1d189121385899215dfcccde1229550f46540e7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XHVOYJMLEJESIDS4CBDKWVZDCX/bundle.json","state_url":"https://pith.science/pith/XHVOYJMLEJESIDS4CBDKWVZDCX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XHVOYJMLEJESIDS4CBDKWVZDCX/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":"2026-08-07T19:13:36Z","links":{"resolver":"https://pith.science/pith/XHVOYJMLEJESIDS4CBDKWVZDCX","bundle":"https://pith.science/pith/XHVOYJMLEJESIDS4CBDKWVZDCX/bundle.json","state":"https://pith.science/pith/XHVOYJMLEJESIDS4CBDKWVZDCX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XHVOYJMLEJESIDS4CBDKWVZDCX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:XHVOYJMLEJESIDS4CBDKWVZDCX","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":"211cdbdd5b541af64a0262d9458b4d2e21b3f7b9ea519521fbd22718f12b129f","cross_cats_sorted":["cs.LG","cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-11-17T13:59:34Z","title_canon_sha256":"64c0370b218e19da60f400314c9eed7d684fe8a89586ff6c5abf69ec7cceb89e"},"schema_version":"1.0","source":{"id":"2211.09536","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.09536","created_at":"2026-07-05T05:42:49Z"},{"alias_kind":"arxiv_version","alias_value":"2211.09536v3","created_at":"2026-07-05T05:42:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.09536","created_at":"2026-07-05T05:42:49Z"},{"alias_kind":"pith_short_12","alias_value":"XHVOYJMLEJES","created_at":"2026-07-05T05:42:49Z"},{"alias_kind":"pith_short_16","alias_value":"XHVOYJMLEJESIDS4","created_at":"2026-07-05T05:42:49Z"},{"alias_kind":"pith_short_8","alias_value":"XHVOYJML","created_at":"2026-07-05T05:42:49Z"}],"graph_snapshots":[{"event_id":"sha256:02a2df7585d325e2e80191c8c1d189121385899215dfcccde1229550f46540e7","target":"graph","created_at":"2026-07-05T05:42:49Z","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/2211.09536/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning based text-to-speech (TTS) systems have been evolving rapidly with advances in model architectures, training methodologies, and generalization across speakers and languages. However, these advances have not been thoroughly investigated for Indian language speech synthesis. Such investigation is computationally expensive given the number and diversity of Indian languages, relatively lower resource availability, and the diverse set of advances in neural TTS that remain untested. In this paper, we evaluate the choice of acoustic models, vocoders, supplementary loss functions, traini","authors_text":"Gokul Karthik Kumar, Karthik Nandakumar, Mitesh M. Khapra, Pratyush Kumar, Praveen S V","cross_cats":["cs.LG","cs.SD","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-11-17T13:59:34Z","title":"Towards Building Text-To-Speech Systems for the Next Billion Users"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.09536","kind":"arxiv","version":3},"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":"sha256:028fa75f1f042fd142a2b59a22f8836816063f17b9e18f58f89f3df0629ad0a8","target":"record","created_at":"2026-07-05T05:42:49Z","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":"211cdbdd5b541af64a0262d9458b4d2e21b3f7b9ea519521fbd22718f12b129f","cross_cats_sorted":["cs.LG","cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-11-17T13:59:34Z","title_canon_sha256":"64c0370b218e19da60f400314c9eed7d684fe8a89586ff6c5abf69ec7cceb89e"},"schema_version":"1.0","source":{"id":"2211.09536","kind":"arxiv","version":3}},"canonical_sha256":"b9eaec258b2249240e5c1046ab572315d13af6fa1f1d95443d95edc503606dc3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b9eaec258b2249240e5c1046ab572315d13af6fa1f1d95443d95edc503606dc3","first_computed_at":"2026-07-05T05:42:49.995456Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:42:49.995456Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8zcViS3Mdu3kOf3fCT2u8VgK5D6/DV14lQJJm+OO5nzuiWBfmejWH+yH7A0DBVDb95fzNNjmMmQemWO62APvBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:42:49.995876Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.09536","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:028fa75f1f042fd142a2b59a22f8836816063f17b9e18f58f89f3df0629ad0a8","sha256:02a2df7585d325e2e80191c8c1d189121385899215dfcccde1229550f46540e7"],"state_sha256":"eaaf22295c1d18c10fad072e38de0eb7b033bad1bd9c7eb7e2b47b5c8b7db38e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jGPIFbOP7DZVf+4p62747cxtq4f6XfcHIQJ7TgpfUpCersaWJHWKxgZvgXIlnJz3FOKkRs78jXyztqBlFtrZCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T19:13:36.409195Z","bundle_sha256":"09bba326017e2dbbec9b1d3f37367e3c137e44c3109be21b10958dec86ff922d"}}