{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:E65EF2IM3UBWA2TWTVG4SBIWYX","short_pith_number":"pith:E65EF2IM","schema_version":"1.0","canonical_sha256":"27ba42e90cdd03606a769d4dc90516c5cd32df2ec20de73500d373c7b2351b2b","source":{"kind":"arxiv","id":"2211.03279","version":1},"attestation_state":"computed","paper":{"title":"A Context-Aware Computational Approach for Measuring Vocal Entrainment in Dyadic Conversations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Catherine Lord, Md Nasir, Rimita Lahiri, Shrikanth Narayanan, So Hyun Kim","submitted_at":"2022-11-07T03:07:37Z","abstract_excerpt":"Vocal entrainment is a social adaptation mechanism in human interaction, knowledge of which can offer useful insights to an individual's cognitive-behavioral characteristics. We propose a context-aware approach for measuring vocal entrainment in dyadic conversations. We use conformers(a combination of convolutional network and transformer) for capturing both short-term and long-term conversational context to model entrainment patterns in interactions across different domains. Specifically we use cross-subject attention layers to learn intra- as well as inter-personal signals from dyadic conver"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2211.03279","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-11-07T03:07:37Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"65b4bbeb2db70a27e4ea8ecc5974d3df07752eb09f219fd8a2bcb82786301ffc","abstract_canon_sha256":"ab0633ec7dbf90085f643188b8c0ebd5dda33604ccecfff2102bb83c173d0594"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:13:47.003766Z","signature_b64":"YYKwKYToWarmfLsDnaUyscZEAymgPweTiAtW6yV03Qst4XonJ92iNJ8+LkbV2tKI1wOiq/yBX8CZqIJ4M2WJCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27ba42e90cdd03606a769d4dc90516c5cd32df2ec20de73500d373c7b2351b2b","last_reissued_at":"2026-07-05T05:13:47.003367Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:13:47.003367Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Context-Aware Computational Approach for Measuring Vocal Entrainment in Dyadic Conversations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Catherine Lord, Md Nasir, Rimita Lahiri, Shrikanth Narayanan, So Hyun Kim","submitted_at":"2022-11-07T03:07:37Z","abstract_excerpt":"Vocal entrainment is a social adaptation mechanism in human interaction, knowledge of which can offer useful insights to an individual's cognitive-behavioral characteristics. We propose a context-aware approach for measuring vocal entrainment in dyadic conversations. We use conformers(a combination of convolutional network and transformer) for capturing both short-term and long-term conversational context to model entrainment patterns in interactions across different domains. Specifically we use cross-subject attention layers to learn intra- as well as inter-personal signals from dyadic conver"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.03279","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/2211.03279/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2211.03279","created_at":"2026-07-05T05:13:47.003430+00:00"},{"alias_kind":"arxiv_version","alias_value":"2211.03279v1","created_at":"2026-07-05T05:13:47.003430+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.03279","created_at":"2026-07-05T05:13:47.003430+00:00"},{"alias_kind":"pith_short_12","alias_value":"E65EF2IM3UBW","created_at":"2026-07-05T05:13:47.003430+00:00"},{"alias_kind":"pith_short_16","alias_value":"E65EF2IM3UBWA2TW","created_at":"2026-07-05T05:13:47.003430+00:00"},{"alias_kind":"pith_short_8","alias_value":"E65EF2IM","created_at":"2026-07-05T05:13:47.003430+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/E65EF2IM3UBWA2TWTVG4SBIWYX","json":"https://pith.science/pith/E65EF2IM3UBWA2TWTVG4SBIWYX.json","graph_json":"https://pith.science/api/pith-number/E65EF2IM3UBWA2TWTVG4SBIWYX/graph.json","events_json":"https://pith.science/api/pith-number/E65EF2IM3UBWA2TWTVG4SBIWYX/events.json","paper":"https://pith.science/paper/E65EF2IM"},"agent_actions":{"view_html":"https://pith.science/pith/E65EF2IM3UBWA2TWTVG4SBIWYX","download_json":"https://pith.science/pith/E65EF2IM3UBWA2TWTVG4SBIWYX.json","view_paper":"https://pith.science/paper/E65EF2IM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2211.03279&json=true","fetch_graph":"https://pith.science/api/pith-number/E65EF2IM3UBWA2TWTVG4SBIWYX/graph.json","fetch_events":"https://pith.science/api/pith-number/E65EF2IM3UBWA2TWTVG4SBIWYX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/E65EF2IM3UBWA2TWTVG4SBIWYX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/E65EF2IM3UBWA2TWTVG4SBIWYX/action/storage_attestation","attest_author":"https://pith.science/pith/E65EF2IM3UBWA2TWTVG4SBIWYX/action/author_attestation","sign_citation":"https://pith.science/pith/E65EF2IM3UBWA2TWTVG4SBIWYX/action/citation_signature","submit_replication":"https://pith.science/pith/E65EF2IM3UBWA2TWTVG4SBIWYX/action/replication_record"}},"created_at":"2026-07-05T05:13:47.003430+00:00","updated_at":"2026-07-05T05:13:47.003430+00:00"}