{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:L2XYIDJG2CS4ESXEPAB3MBKMTA","short_pith_number":"pith:L2XYIDJG","canonical_record":{"source":{"id":"2409.16920","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2024-09-25T13:27:17Z","cross_cats_sorted":["cs.AI","cs.CL","cs.HC","cs.SD"],"title_canon_sha256":"63bcff7cb9fe8c010c62c804468039c2e19776eda54e9e34d4ecc0b839c2318c","abstract_canon_sha256":"5f9b24ab4d8379fbd5b9d230b5eb61e3459bbe947739c2cec05a4e5f472fe513"},"schema_version":"1.0"},"canonical_sha256":"5eaf840d26d0a5c24ae47803b6054c980f92a745f4eec8bb49e2fa021041c9ac","source":{"kind":"arxiv","id":"2409.16920","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.16920","created_at":"2026-07-05T10:56:09Z"},{"alias_kind":"arxiv_version","alias_value":"2409.16920v2","created_at":"2026-07-05T10:56:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.16920","created_at":"2026-07-05T10:56:09Z"},{"alias_kind":"pith_short_12","alias_value":"L2XYIDJG2CS4","created_at":"2026-07-05T10:56:09Z"},{"alias_kind":"pith_short_16","alias_value":"L2XYIDJG2CS4ESXE","created_at":"2026-07-05T10:56:09Z"},{"alias_kind":"pith_short_8","alias_value":"L2XYIDJG","created_at":"2026-07-05T10:56:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:L2XYIDJG2CS4ESXEPAB3MBKMTA","target":"record","payload":{"canonical_record":{"source":{"id":"2409.16920","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2024-09-25T13:27:17Z","cross_cats_sorted":["cs.AI","cs.CL","cs.HC","cs.SD"],"title_canon_sha256":"63bcff7cb9fe8c010c62c804468039c2e19776eda54e9e34d4ecc0b839c2318c","abstract_canon_sha256":"5f9b24ab4d8379fbd5b9d230b5eb61e3459bbe947739c2cec05a4e5f472fe513"},"schema_version":"1.0"},"canonical_sha256":"5eaf840d26d0a5c24ae47803b6054c980f92a745f4eec8bb49e2fa021041c9ac","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:56:09.065176Z","signature_b64":"lzWkKpf9GfM0vMn/UdtVoZTpfJTksG8uSV+kZtErijD/BKYKsFXa35wVRyYJRPgE7IEEnwD38hnDP37kmVV4Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5eaf840d26d0a5c24ae47803b6054c980f92a745f4eec8bb49e2fa021041c9ac","last_reissued_at":"2026-07-05T10:56:09.064666Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:56:09.064666Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.16920","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":"2026-07-05T10:56:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YoyXGQFFzy79eSAYmGQB8W5kSmp6/XwsGCl6Bagt0tdcReEWGhAj55L5wPA784hBKYEY95wLmLXRcLj6hL2WBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T08:51:05.256571Z"},"content_sha256":"a06f32ae068f4fb1790009f0ea09f987f8c7a88dba4dd2263a26b1e9d93c30db","schema_version":"1.0","event_id":"sha256:a06f32ae068f4fb1790009f0ea09f987f8c7a88dba4dd2263a26b1e9d93c30db"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:L2XYIDJG2CS4ESXEPAB3MBKMTA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Cross-Lingual Speech Emotion Recognition: Humans vs. Self-Supervised Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.HC","cs.SD"],"primary_cat":"eess.AS","authors_text":"Hui Feng, Jiahong Yuan, Korin Richmond, Tianqi Geng, Yuanchao Li, Zhichen Han","submitted_at":"2024-09-25T13:27:17Z","abstract_excerpt":"Utilizing Self-Supervised Learning (SSL) models for Speech Emotion Recognition (SER) has proven effective, yet limited research has explored cross-lingual scenarios. This study presents a comparative analysis between human performance and SSL models, beginning with a layer-wise analysis and an exploration of parameter-efficient fine-tuning strategies in monolingual, cross-lingual, and transfer learning contexts. We further compare the SER ability of models and humans at both utterance- and segment-levels. Additionally, we investigate the impact of dialect on cross-lingual SER through human eva"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.16920","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/2409.16920/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":"2026-07-05T10:56:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I5gkkCnR0/kncAEJS4dXWnR9w6klVarodosahbbPGfzltZFLcxE9vcwt25a46YNeZMdLUkbe6U0RcvW3ueMHAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T08:51:05.256947Z"},"content_sha256":"6a630fa733d99fb6e4979c4734af7d164717827b551c5370ade83b441a2d4954","schema_version":"1.0","event_id":"sha256:6a630fa733d99fb6e4979c4734af7d164717827b551c5370ade83b441a2d4954"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L2XYIDJG2CS4ESXEPAB3MBKMTA/bundle.json","state_url":"https://pith.science/pith/L2XYIDJG2CS4ESXEPAB3MBKMTA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L2XYIDJG2CS4ESXEPAB3MBKMTA/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":"2026-07-13T08:51:05Z","links":{"resolver":"https://pith.science/pith/L2XYIDJG2CS4ESXEPAB3MBKMTA","bundle":"https://pith.science/pith/L2XYIDJG2CS4ESXEPAB3MBKMTA/bundle.json","state":"https://pith.science/pith/L2XYIDJG2CS4ESXEPAB3MBKMTA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L2XYIDJG2CS4ESXEPAB3MBKMTA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:L2XYIDJG2CS4ESXEPAB3MBKMTA","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":"5f9b24ab4d8379fbd5b9d230b5eb61e3459bbe947739c2cec05a4e5f472fe513","cross_cats_sorted":["cs.AI","cs.CL","cs.HC","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2024-09-25T13:27:17Z","title_canon_sha256":"63bcff7cb9fe8c010c62c804468039c2e19776eda54e9e34d4ecc0b839c2318c"},"schema_version":"1.0","source":{"id":"2409.16920","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.16920","created_at":"2026-07-05T10:56:09Z"},{"alias_kind":"arxiv_version","alias_value":"2409.16920v2","created_at":"2026-07-05T10:56:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.16920","created_at":"2026-07-05T10:56:09Z"},{"alias_kind":"pith_short_12","alias_value":"L2XYIDJG2CS4","created_at":"2026-07-05T10:56:09Z"},{"alias_kind":"pith_short_16","alias_value":"L2XYIDJG2CS4ESXE","created_at":"2026-07-05T10:56:09Z"},{"alias_kind":"pith_short_8","alias_value":"L2XYIDJG","created_at":"2026-07-05T10:56:09Z"}],"graph_snapshots":[{"event_id":"sha256:6a630fa733d99fb6e4979c4734af7d164717827b551c5370ade83b441a2d4954","target":"graph","created_at":"2026-07-05T10:56:09Z","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/2409.16920/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Utilizing Self-Supervised Learning (SSL) models for Speech Emotion Recognition (SER) has proven effective, yet limited research has explored cross-lingual scenarios. This study presents a comparative analysis between human performance and SSL models, beginning with a layer-wise analysis and an exploration of parameter-efficient fine-tuning strategies in monolingual, cross-lingual, and transfer learning contexts. We further compare the SER ability of models and humans at both utterance- and segment-levels. Additionally, we investigate the impact of dialect on cross-lingual SER through human eva","authors_text":"Hui Feng, Jiahong Yuan, Korin Richmond, Tianqi Geng, Yuanchao Li, Zhichen Han","cross_cats":["cs.AI","cs.CL","cs.HC","cs.SD"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2024-09-25T13:27:17Z","title":"Cross-Lingual Speech Emotion Recognition: Humans vs. Self-Supervised Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.16920","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:a06f32ae068f4fb1790009f0ea09f987f8c7a88dba4dd2263a26b1e9d93c30db","target":"record","created_at":"2026-07-05T10:56:09Z","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":"5f9b24ab4d8379fbd5b9d230b5eb61e3459bbe947739c2cec05a4e5f472fe513","cross_cats_sorted":["cs.AI","cs.CL","cs.HC","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2024-09-25T13:27:17Z","title_canon_sha256":"63bcff7cb9fe8c010c62c804468039c2e19776eda54e9e34d4ecc0b839c2318c"},"schema_version":"1.0","source":{"id":"2409.16920","kind":"arxiv","version":2}},"canonical_sha256":"5eaf840d26d0a5c24ae47803b6054c980f92a745f4eec8bb49e2fa021041c9ac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5eaf840d26d0a5c24ae47803b6054c980f92a745f4eec8bb49e2fa021041c9ac","first_computed_at":"2026-07-05T10:56:09.064666Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:56:09.064666Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lzWkKpf9GfM0vMn/UdtVoZTpfJTksG8uSV+kZtErijD/BKYKsFXa35wVRyYJRPgE7IEEnwD38hnDP37kmVV4Aw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:56:09.065176Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.16920","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a06f32ae068f4fb1790009f0ea09f987f8c7a88dba4dd2263a26b1e9d93c30db","sha256:6a630fa733d99fb6e4979c4734af7d164717827b551c5370ade83b441a2d4954"],"state_sha256":"44b4e4569a4d1d3cf0848c333c90f57f11e7353f1512c793544514dccf254938"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XIkc3CcBtHaFUYcQNvupMTbzWGOx8kPsEYgccT4aGgRGmGX8Krrpn9oJ52NS5CUZMcl6vJFsp/MmDiZx6RDXCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-13T08:51:05.259121Z","bundle_sha256":"5635107bc0fceee8cd4618706ec54f2cb54859d7e5a55baecfa8050798b833be"}}