{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:W3ZDYWZBYHTPBFR5WCW3M4QP4Q","short_pith_number":"pith:W3ZDYWZB","canonical_record":{"source":{"id":"2401.09512","kind":"arxiv","version":10},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-01-17T15:09:02Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"ebf279013df461631f15b7800fdcb41ad504c4b7e8e01dfbb3d84dd2a8f99b57","abstract_canon_sha256":"72c410db9ebc2a668dd5387b9700a46eba03c3d55aa6f97968110081db20518e"},"schema_version":"1.0"},"canonical_sha256":"b6f23c5b21c1e6f0963db0adb6720fe403412c2d537f0aea5ab4cfca4de8810a","source":{"kind":"arxiv","id":"2401.09512","version":10},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.09512","created_at":"2026-05-20T00:05:25Z"},{"alias_kind":"arxiv_version","alias_value":"2401.09512v10","created_at":"2026-05-20T00:05:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.09512","created_at":"2026-05-20T00:05:25Z"},{"alias_kind":"pith_short_12","alias_value":"W3ZDYWZBYHTP","created_at":"2026-05-20T00:05:25Z"},{"alias_kind":"pith_short_16","alias_value":"W3ZDYWZBYHTPBFR5","created_at":"2026-05-20T00:05:25Z"},{"alias_kind":"pith_short_8","alias_value":"W3ZDYWZB","created_at":"2026-05-20T00:05:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:W3ZDYWZBYHTPBFR5WCW3M4QP4Q","target":"record","payload":{"canonical_record":{"source":{"id":"2401.09512","kind":"arxiv","version":10},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-01-17T15:09:02Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"ebf279013df461631f15b7800fdcb41ad504c4b7e8e01dfbb3d84dd2a8f99b57","abstract_canon_sha256":"72c410db9ebc2a668dd5387b9700a46eba03c3d55aa6f97968110081db20518e"},"schema_version":"1.0"},"canonical_sha256":"b6f23c5b21c1e6f0963db0adb6720fe403412c2d537f0aea5ab4cfca4de8810a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:05:25.095249Z","signature_b64":"280/10L+DTLIg/8txKTBp4KiPB40tXQlAoL86E7xo662T4L/r8qB/Y8l4gY5ZPO4Tuq2U/XnMP8yu5KJXAvWCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b6f23c5b21c1e6f0963db0adb6720fe403412c2d537f0aea5ab4cfca4de8810a","last_reissued_at":"2026-05-20T00:05:25.094370Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:05:25.094370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.09512","source_version":10,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:05:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zqe85Wo6oqMS+n7AiQcAN4sZKVtLqLJRk0XJEqviDWmr71xzTCKksu/3x2bHC930yfKto1xHTxz7aaGoYievBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-24T12:56:22.350060Z"},"content_sha256":"441da9d036f26356eb3cf2e2d7763ea554fab4ae5c1b9cb36baeda63773109eb","schema_version":"1.0","event_id":"sha256:441da9d036f26356eb3cf2e2d7763ea554fab4ae5c1b9cb36baeda63773109eb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:W3ZDYWZBYHTPBFR5WCW3M4QP4Q","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MLAAD: The Multi-Language Audio Anti-Spoofing Dataset","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.SD","authors_text":"Edresson Casanova, Eren G\\\"olge, Konstantin B\\\"ottinger, Nicolas M. M\\\"uller, Philip Sperl, Piotr Kawa, Piotr Syga, Thorsten M\\\"uller, Wei Herng Choong","submitted_at":"2024-01-17T15:09:02Z","abstract_excerpt":"This paper presents the Multi-Language Audio Anti-Spoofing Dataset (MLAAD), version 10: a dataset of synthetic audio to train and evaluate audio deepfake detection models. It features 175 Text-to-Speech (TTS) models, comprising a total of 1002.9 hours of synthetic voice in 54 different languages. To evaluate this dataset, we train three state-of-the-art deepfake detection models with MLAAD and observe that it demonstrates superior performance to comparable datasets like InTheWild and FakeOrReal when used as a training resource. Moreover, compared to the renowned ASVspoof 2019 dataset, MLAAD pr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.09512","kind":"arxiv","version":10},"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/2401.09512/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":"2026-05-20T00:05:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a3/FdKdvYYMlrZXICs4CSWglD+hf3Nad1WGnATWdDFAmSd6kV96q6V4S+djFJX0f7GiWkE16AaWUFgtuIK6YDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-24T12:56:22.350770Z"},"content_sha256":"dcff9c1e264052d84838c865eb501841c467eca1b8b0c2652c20bde011e1fa4b","schema_version":"1.0","event_id":"sha256:dcff9c1e264052d84838c865eb501841c467eca1b8b0c2652c20bde011e1fa4b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W3ZDYWZBYHTPBFR5WCW3M4QP4Q/bundle.json","state_url":"https://pith.science/pith/W3ZDYWZBYHTPBFR5WCW3M4QP4Q/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W3ZDYWZBYHTPBFR5WCW3M4QP4Q/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":"2026-05-24T12:56:22Z","links":{"resolver":"https://pith.science/pith/W3ZDYWZBYHTPBFR5WCW3M4QP4Q","bundle":"https://pith.science/pith/W3ZDYWZBYHTPBFR5WCW3M4QP4Q/bundle.json","state":"https://pith.science/pith/W3ZDYWZBYHTPBFR5WCW3M4QP4Q/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W3ZDYWZBYHTPBFR5WCW3M4QP4Q/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:W3ZDYWZBYHTPBFR5WCW3M4QP4Q","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":"72c410db9ebc2a668dd5387b9700a46eba03c3d55aa6f97968110081db20518e","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-01-17T15:09:02Z","title_canon_sha256":"ebf279013df461631f15b7800fdcb41ad504c4b7e8e01dfbb3d84dd2a8f99b57"},"schema_version":"1.0","source":{"id":"2401.09512","kind":"arxiv","version":10}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.09512","created_at":"2026-05-20T00:05:25Z"},{"alias_kind":"arxiv_version","alias_value":"2401.09512v10","created_at":"2026-05-20T00:05:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.09512","created_at":"2026-05-20T00:05:25Z"},{"alias_kind":"pith_short_12","alias_value":"W3ZDYWZBYHTP","created_at":"2026-05-20T00:05:25Z"},{"alias_kind":"pith_short_16","alias_value":"W3ZDYWZBYHTPBFR5","created_at":"2026-05-20T00:05:25Z"},{"alias_kind":"pith_short_8","alias_value":"W3ZDYWZB","created_at":"2026-05-20T00:05:25Z"}],"graph_snapshots":[{"event_id":"sha256:dcff9c1e264052d84838c865eb501841c467eca1b8b0c2652c20bde011e1fa4b","target":"graph","created_at":"2026-05-20T00:05:25Z","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/2401.09512/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper presents the Multi-Language Audio Anti-Spoofing Dataset (MLAAD), version 10: a dataset of synthetic audio to train and evaluate audio deepfake detection models. It features 175 Text-to-Speech (TTS) models, comprising a total of 1002.9 hours of synthetic voice in 54 different languages. To evaluate this dataset, we train three state-of-the-art deepfake detection models with MLAAD and observe that it demonstrates superior performance to comparable datasets like InTheWild and FakeOrReal when used as a training resource. Moreover, compared to the renowned ASVspoof 2019 dataset, MLAAD pr","authors_text":"Edresson Casanova, Eren G\\\"olge, Konstantin B\\\"ottinger, Nicolas M. M\\\"uller, Philip Sperl, Piotr Kawa, Piotr Syga, Thorsten M\\\"uller, Wei Herng Choong","cross_cats":["eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-01-17T15:09:02Z","title":"MLAAD: The Multi-Language Audio Anti-Spoofing Dataset"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.09512","kind":"arxiv","version":10},"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":"sha256:441da9d036f26356eb3cf2e2d7763ea554fab4ae5c1b9cb36baeda63773109eb","target":"record","created_at":"2026-05-20T00:05:25Z","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":"72c410db9ebc2a668dd5387b9700a46eba03c3d55aa6f97968110081db20518e","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2024-01-17T15:09:02Z","title_canon_sha256":"ebf279013df461631f15b7800fdcb41ad504c4b7e8e01dfbb3d84dd2a8f99b57"},"schema_version":"1.0","source":{"id":"2401.09512","kind":"arxiv","version":10}},"canonical_sha256":"b6f23c5b21c1e6f0963db0adb6720fe403412c2d537f0aea5ab4cfca4de8810a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b6f23c5b21c1e6f0963db0adb6720fe403412c2d537f0aea5ab4cfca4de8810a","first_computed_at":"2026-05-20T00:05:25.094370Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:05:25.094370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"280/10L+DTLIg/8txKTBp4KiPB40tXQlAoL86E7xo662T4L/r8qB/Y8l4gY5ZPO4Tuq2U/XnMP8yu5KJXAvWCw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:05:25.095249Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.09512","source_kind":"arxiv","source_version":10}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:441da9d036f26356eb3cf2e2d7763ea554fab4ae5c1b9cb36baeda63773109eb","sha256:dcff9c1e264052d84838c865eb501841c467eca1b8b0c2652c20bde011e1fa4b"],"state_sha256":"44357894a7d9ddaf57b5fd8b72093e0e4de3255ba7ca1a6405812048a6be4e80"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6AQpKDMtX/Myp9nrH+pFYQ3iv6lguRJP9nZMKXZAhwO4j6hEQSfEA47y1W4sZ/rlqE5878eHFJ6sdhKcg7E9Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-24T12:56:22.354171Z","bundle_sha256":"3a79f288bfc00bd701e2d7341d9f9363f7d958acebf04037b1dd5d4f8d0a0f17"}}