{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:MYBQRFSIEZHN3R7U4BEYH7DTGO","short_pith_number":"pith:MYBQRFSI","canonical_record":{"source":{"id":"1903.12094","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-28T16:19:20Z","cross_cats_sorted":["cs.SD","eess.AS","stat.ML"],"title_canon_sha256":"e8a01fa35f2554533892fb8594020e46074781c40d80df7ad9aee6bee267f55e","abstract_canon_sha256":"c483df48ca41cc47c90f619fe9218df571244259379d9cb507b509f364ea7719"},"schema_version":"1.0"},"canonical_sha256":"6603089648264eddc7f4e04983fc7333a5109248aa3de8dde9dad5eceffc1546","source":{"kind":"arxiv","id":"1903.12094","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.12094","created_at":"2026-07-05T00:16:33Z"},{"alias_kind":"arxiv_version","alias_value":"1903.12094v2","created_at":"2026-07-05T00:16:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.12094","created_at":"2026-07-05T00:16:33Z"},{"alias_kind":"pith_short_12","alias_value":"MYBQRFSIEZHN","created_at":"2026-07-05T00:16:33Z"},{"alias_kind":"pith_short_16","alias_value":"MYBQRFSIEZHN3R7U","created_at":"2026-07-05T00:16:33Z"},{"alias_kind":"pith_short_8","alias_value":"MYBQRFSI","created_at":"2026-07-05T00:16:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:MYBQRFSIEZHN3R7U4BEYH7DTGO","target":"record","payload":{"canonical_record":{"source":{"id":"1903.12094","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-28T16:19:20Z","cross_cats_sorted":["cs.SD","eess.AS","stat.ML"],"title_canon_sha256":"e8a01fa35f2554533892fb8594020e46074781c40d80df7ad9aee6bee267f55e","abstract_canon_sha256":"c483df48ca41cc47c90f619fe9218df571244259379d9cb507b509f364ea7719"},"schema_version":"1.0"},"canonical_sha256":"6603089648264eddc7f4e04983fc7333a5109248aa3de8dde9dad5eceffc1546","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:16:33.380201Z","signature_b64":"t5VsQdmRLRc/BH3jl2pU0KuqSvJG3vuNtit/64ODYoofsojR4fpw4IgvZkPbFifgwDIDcXG5lgCz0yimcZqTBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6603089648264eddc7f4e04983fc7333a5109248aa3de8dde9dad5eceffc1546","last_reissued_at":"2026-07-05T00:16:33.379809Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:16:33.379809Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.12094","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":"2026-07-05T00:16:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"40Bn6lw9tYUswytDLPIYUTMrx2W6QUIbcG4WuZsCb+DxLSsInlKwXY6W4ulSX4eYt8IMEhDCoWLu1gWicHQOAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T22:57:31.495354Z"},"content_sha256":"d9afb7f4c46a2509215f5451be53bd22cd8af3e68d0c3c1b13fedc1e9a47e48a","schema_version":"1.0","event_id":"sha256:d9afb7f4c46a2509215f5451be53bd22cd8af3e68d0c3c1b13fedc1e9a47e48a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:MYBQRFSIEZHN3R7U4BEYH7DTGO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SD","eess.AS","stat.ML"],"primary_cat":"cs.LG","authors_text":"Emily Mower Provost, John Gideon, Melvin G McInnis","submitted_at":"2019-03-28T16:19:20Z","abstract_excerpt":"Automatic speech emotion recognition provides computers with critical context to enable user understanding. While methods trained and tested within the same dataset have been shown successful, they often fail when applied to unseen datasets. To address this, recent work has focused on adversarial methods to find more generalized representations of emotional speech. However, many of these methods have issues converging, and only involve datasets collected in laboratory conditions. In this paper, we introduce Adversarial Discriminative Domain Generalization (ADDoG), which follows an easier to tr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.12094","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/1903.12094/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":"2026-07-05T00:16:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TEjZQWbELqXlbQGb2WWOQfxSNqjAIP/e4mdBa5K6BkQTvdzFeFaxQ21NUZIsjQ545x8MhA2bsTpfegysohnjAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T22:57:31.495927Z"},"content_sha256":"b8d0c4b26ddca43888b6193fc518862ca99720e304cfd390c16600b9378f6000","schema_version":"1.0","event_id":"sha256:b8d0c4b26ddca43888b6193fc518862ca99720e304cfd390c16600b9378f6000"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MYBQRFSIEZHN3R7U4BEYH7DTGO/bundle.json","state_url":"https://pith.science/pith/MYBQRFSIEZHN3R7U4BEYH7DTGO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MYBQRFSIEZHN3R7U4BEYH7DTGO/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":"2026-08-06T22:57:31Z","links":{"resolver":"https://pith.science/pith/MYBQRFSIEZHN3R7U4BEYH7DTGO","bundle":"https://pith.science/pith/MYBQRFSIEZHN3R7U4BEYH7DTGO/bundle.json","state":"https://pith.science/pith/MYBQRFSIEZHN3R7U4BEYH7DTGO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MYBQRFSIEZHN3R7U4BEYH7DTGO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:MYBQRFSIEZHN3R7U4BEYH7DTGO","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":"c483df48ca41cc47c90f619fe9218df571244259379d9cb507b509f364ea7719","cross_cats_sorted":["cs.SD","eess.AS","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-28T16:19:20Z","title_canon_sha256":"e8a01fa35f2554533892fb8594020e46074781c40d80df7ad9aee6bee267f55e"},"schema_version":"1.0","source":{"id":"1903.12094","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.12094","created_at":"2026-07-05T00:16:33Z"},{"alias_kind":"arxiv_version","alias_value":"1903.12094v2","created_at":"2026-07-05T00:16:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.12094","created_at":"2026-07-05T00:16:33Z"},{"alias_kind":"pith_short_12","alias_value":"MYBQRFSIEZHN","created_at":"2026-07-05T00:16:33Z"},{"alias_kind":"pith_short_16","alias_value":"MYBQRFSIEZHN3R7U","created_at":"2026-07-05T00:16:33Z"},{"alias_kind":"pith_short_8","alias_value":"MYBQRFSI","created_at":"2026-07-05T00:16:33Z"}],"graph_snapshots":[{"event_id":"sha256:b8d0c4b26ddca43888b6193fc518862ca99720e304cfd390c16600b9378f6000","target":"graph","created_at":"2026-07-05T00:16:33Z","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/1903.12094/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automatic speech emotion recognition provides computers with critical context to enable user understanding. While methods trained and tested within the same dataset have been shown successful, they often fail when applied to unseen datasets. To address this, recent work has focused on adversarial methods to find more generalized representations of emotional speech. However, many of these methods have issues converging, and only involve datasets collected in laboratory conditions. In this paper, we introduce Adversarial Discriminative Domain Generalization (ADDoG), which follows an easier to tr","authors_text":"Emily Mower Provost, John Gideon, Melvin G McInnis","cross_cats":["cs.SD","eess.AS","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-28T16:19:20Z","title":"Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.12094","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:d9afb7f4c46a2509215f5451be53bd22cd8af3e68d0c3c1b13fedc1e9a47e48a","target":"record","created_at":"2026-07-05T00:16:33Z","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":"c483df48ca41cc47c90f619fe9218df571244259379d9cb507b509f364ea7719","cross_cats_sorted":["cs.SD","eess.AS","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-28T16:19:20Z","title_canon_sha256":"e8a01fa35f2554533892fb8594020e46074781c40d80df7ad9aee6bee267f55e"},"schema_version":"1.0","source":{"id":"1903.12094","kind":"arxiv","version":2}},"canonical_sha256":"6603089648264eddc7f4e04983fc7333a5109248aa3de8dde9dad5eceffc1546","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6603089648264eddc7f4e04983fc7333a5109248aa3de8dde9dad5eceffc1546","first_computed_at":"2026-07-05T00:16:33.379809Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:16:33.379809Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"t5VsQdmRLRc/BH3jl2pU0KuqSvJG3vuNtit/64ODYoofsojR4fpw4IgvZkPbFifgwDIDcXG5lgCz0yimcZqTBA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:16:33.380201Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.12094","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d9afb7f4c46a2509215f5451be53bd22cd8af3e68d0c3c1b13fedc1e9a47e48a","sha256:b8d0c4b26ddca43888b6193fc518862ca99720e304cfd390c16600b9378f6000"],"state_sha256":"e4291b4a505a3150d31380b2e4d388a9a73eb5996552a3aab119a88d55d28c7b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QE3vlK2aTjA+HM0j53r/rKqZV9PQVqaxlfy8MJ28YVTpznUHcUAj+awZR9IX1l8hNizAKGaRzLX6waYo68LnDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T22:57:31.501057Z","bundle_sha256":"8db08cdd7ccc7b608a38db93d721b0c6ca5adb3961e632695ce8866bd21dff9b"}}