{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:YVB6ZKDX2H6S6BTIQABRXJCKXQ","short_pith_number":"pith:YVB6ZKDX","canonical_record":{"source":{"id":"2203.14865","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-03-28T16:14:08Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"80c6e3b8e5027cf188059f4df84e69a55f24a370b3a979febad0e8d41724cee0","abstract_canon_sha256":"a2e90d846fca1076c1b7af6994031ec0f42ceb7ed1f11d6ce0ff16f3f128590c"},"schema_version":"1.0"},"canonical_sha256":"c543eca877d1fd2f066880031ba44abc01d6db579a70a426f9731a0ebe5133b9","source":{"kind":"arxiv","id":"2203.14865","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.14865","created_at":"2026-07-05T04:09:09Z"},{"alias_kind":"arxiv_version","alias_value":"2203.14865v1","created_at":"2026-07-05T04:09:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.14865","created_at":"2026-07-05T04:09:09Z"},{"alias_kind":"pith_short_12","alias_value":"YVB6ZKDX2H6S","created_at":"2026-07-05T04:09:09Z"},{"alias_kind":"pith_short_16","alias_value":"YVB6ZKDX2H6S6BTI","created_at":"2026-07-05T04:09:09Z"},{"alias_kind":"pith_short_8","alias_value":"YVB6ZKDX","created_at":"2026-07-05T04:09:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:YVB6ZKDX2H6S6BTIQABRXJCKXQ","target":"record","payload":{"canonical_record":{"source":{"id":"2203.14865","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-03-28T16:14:08Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"80c6e3b8e5027cf188059f4df84e69a55f24a370b3a979febad0e8d41724cee0","abstract_canon_sha256":"a2e90d846fca1076c1b7af6994031ec0f42ceb7ed1f11d6ce0ff16f3f128590c"},"schema_version":"1.0"},"canonical_sha256":"c543eca877d1fd2f066880031ba44abc01d6db579a70a426f9731a0ebe5133b9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:09:09.759384Z","signature_b64":"1DWhGvDcLBUdTGHeRWLTAtL2LnFPBBSb46SqS3EneWWk4LVrcUarF3hAsWF2ANdDyI/MpbmAkZlu4zzzhq5nCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c543eca877d1fd2f066880031ba44abc01d6db579a70a426f9731a0ebe5133b9","last_reissued_at":"2026-07-05T04:09:09.758984Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:09:09.758984Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.14865","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":"2026-07-05T04:09:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k/YNORgNQwnR4+ixSALrtee7JBuCCgiK5JJmNNMmkmw59GYNxi9ZRWIw51t2NIS8xkaCz+ov6hH9FFvLj1QyBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T07:03:41.373631Z"},"content_sha256":"6e990e8b1ad334b5e7636be2f3b2afe9c2092d8aee155b4c23cd74bd8c0501a8","schema_version":"1.0","event_id":"sha256:6e990e8b1ad334b5e7636be2f3b2afe9c2092d8aee155b4c23cd74bd8c0501a8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:YVB6ZKDX2H6S6BTIQABRXJCKXQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Transferable Speech Emotion Representation: On loss functions for cross-lingual latent representations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Anne Katrine Pagsberg, Line H. Clemmensen, Nicole Nadine L{\\o}nfeldt, Sneha Das","submitted_at":"2022-03-28T16:14:08Z","abstract_excerpt":"In recent years, speech emotion recognition (SER) has been used in wide ranging applications, from healthcare to the commercial sector. In addition to signal processing approaches, methods for SER now also use deep learning techniques which provide transfer learning possibilities. However, generalizing over languages, corpora and recording conditions is still an open challenge. In this work we address this gap by exploring loss functions that aid in transferability, specifically to non-tonal languages. We propose a variational autoencoder (VAE) with KL annealing and a semi-supervised VAE to ob"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.14865","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/2203.14865/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":"2026-07-05T04:09:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bz+ckVBVo4K6zmvIS0I2lXe0RquYdM4c4NAdp+BfDf7I5z1J0fg69sx2ogOEyJK6fm3wnfF2sjxlQY8NmJL6DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T07:03:41.374139Z"},"content_sha256":"763a0251e2ab3032f138653b5308ecf89d5cc4313bf0a23c3ded34057180272b","schema_version":"1.0","event_id":"sha256:763a0251e2ab3032f138653b5308ecf89d5cc4313bf0a23c3ded34057180272b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YVB6ZKDX2H6S6BTIQABRXJCKXQ/bundle.json","state_url":"https://pith.science/pith/YVB6ZKDX2H6S6BTIQABRXJCKXQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YVB6ZKDX2H6S6BTIQABRXJCKXQ/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":"2026-08-05T07:03:41Z","links":{"resolver":"https://pith.science/pith/YVB6ZKDX2H6S6BTIQABRXJCKXQ","bundle":"https://pith.science/pith/YVB6ZKDX2H6S6BTIQABRXJCKXQ/bundle.json","state":"https://pith.science/pith/YVB6ZKDX2H6S6BTIQABRXJCKXQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YVB6ZKDX2H6S6BTIQABRXJCKXQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:YVB6ZKDX2H6S6BTIQABRXJCKXQ","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":"a2e90d846fca1076c1b7af6994031ec0f42ceb7ed1f11d6ce0ff16f3f128590c","cross_cats_sorted":["cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-03-28T16:14:08Z","title_canon_sha256":"80c6e3b8e5027cf188059f4df84e69a55f24a370b3a979febad0e8d41724cee0"},"schema_version":"1.0","source":{"id":"2203.14865","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.14865","created_at":"2026-07-05T04:09:09Z"},{"alias_kind":"arxiv_version","alias_value":"2203.14865v1","created_at":"2026-07-05T04:09:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.14865","created_at":"2026-07-05T04:09:09Z"},{"alias_kind":"pith_short_12","alias_value":"YVB6ZKDX2H6S","created_at":"2026-07-05T04:09:09Z"},{"alias_kind":"pith_short_16","alias_value":"YVB6ZKDX2H6S6BTI","created_at":"2026-07-05T04:09:09Z"},{"alias_kind":"pith_short_8","alias_value":"YVB6ZKDX","created_at":"2026-07-05T04:09:09Z"}],"graph_snapshots":[{"event_id":"sha256:763a0251e2ab3032f138653b5308ecf89d5cc4313bf0a23c3ded34057180272b","target":"graph","created_at":"2026-07-05T04:09:09Z","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/2203.14865/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, speech emotion recognition (SER) has been used in wide ranging applications, from healthcare to the commercial sector. In addition to signal processing approaches, methods for SER now also use deep learning techniques which provide transfer learning possibilities. However, generalizing over languages, corpora and recording conditions is still an open challenge. In this work we address this gap by exploring loss functions that aid in transferability, specifically to non-tonal languages. We propose a variational autoencoder (VAE) with KL annealing and a semi-supervised VAE to ob","authors_text":"Anne Katrine Pagsberg, Line H. Clemmensen, Nicole Nadine L{\\o}nfeldt, Sneha Das","cross_cats":["cs.SD"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-03-28T16:14:08Z","title":"Towards Transferable Speech Emotion Representation: On loss functions for cross-lingual latent representations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.14865","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":"sha256:6e990e8b1ad334b5e7636be2f3b2afe9c2092d8aee155b4c23cd74bd8c0501a8","target":"record","created_at":"2026-07-05T04:09:09Z","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":"a2e90d846fca1076c1b7af6994031ec0f42ceb7ed1f11d6ce0ff16f3f128590c","cross_cats_sorted":["cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-03-28T16:14:08Z","title_canon_sha256":"80c6e3b8e5027cf188059f4df84e69a55f24a370b3a979febad0e8d41724cee0"},"schema_version":"1.0","source":{"id":"2203.14865","kind":"arxiv","version":1}},"canonical_sha256":"c543eca877d1fd2f066880031ba44abc01d6db579a70a426f9731a0ebe5133b9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c543eca877d1fd2f066880031ba44abc01d6db579a70a426f9731a0ebe5133b9","first_computed_at":"2026-07-05T04:09:09.758984Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:09:09.758984Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1DWhGvDcLBUdTGHeRWLTAtL2LnFPBBSb46SqS3EneWWk4LVrcUarF3hAsWF2ANdDyI/MpbmAkZlu4zzzhq5nCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:09:09.759384Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.14865","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6e990e8b1ad334b5e7636be2f3b2afe9c2092d8aee155b4c23cd74bd8c0501a8","sha256:763a0251e2ab3032f138653b5308ecf89d5cc4313bf0a23c3ded34057180272b"],"state_sha256":"a634c74a695bf9e846aa6802c5f6cb80eb4d9aebd6cf1e18f58969131a34c00a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZYb6hmXUVFyMkmTtXkefT1bk+LkiBaSO2axjszC/ecvPZuIBl8W3zYLjOgBb3XyuzC/ypgvRRS6i5wqh8CEuCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T07:03:41.379505Z","bundle_sha256":"7cfa96b38cd95af315d6bea3bb962c65063e8a00f659b10ddf97ac25efe4f04b"}}