{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:FEFLTZNWRJOU7WL2VOHE4ICNDK","short_pith_number":"pith:FEFLTZNW","canonical_record":{"source":{"id":"1804.08782","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2018-04-23T23:45:30Z","cross_cats_sorted":["cs.CL","cs.SD"],"title_canon_sha256":"a9de1fd605ea30f7afdd4dadc1dae9655d391befd752aef6f096211823023aab","abstract_canon_sha256":"697e9a801a098bcfe95498dc614d3741027d960d4a4d5024acb15c04014e3c1b"},"schema_version":"1.0"},"canonical_sha256":"290ab9e5b68a5d4fd97aab8e4e204d1a86ec4c0731d2d3f8c331f43117a5ecca","source":{"kind":"arxiv","id":"1804.08782","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.08782","created_at":"2026-05-17T23:48:45Z"},{"alias_kind":"arxiv_version","alias_value":"1804.08782v1","created_at":"2026-05-17T23:48:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.08782","created_at":"2026-05-17T23:48:45Z"},{"alias_kind":"pith_short_12","alias_value":"FEFLTZNWRJOU","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"FEFLTZNWRJOU7WL2","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"FEFLTZNW","created_at":"2026-05-18T12:32:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:FEFLTZNWRJOU7WL2VOHE4ICNDK","target":"record","payload":{"canonical_record":{"source":{"id":"1804.08782","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2018-04-23T23:45:30Z","cross_cats_sorted":["cs.CL","cs.SD"],"title_canon_sha256":"a9de1fd605ea30f7afdd4dadc1dae9655d391befd752aef6f096211823023aab","abstract_canon_sha256":"697e9a801a098bcfe95498dc614d3741027d960d4a4d5024acb15c04014e3c1b"},"schema_version":"1.0"},"canonical_sha256":"290ab9e5b68a5d4fd97aab8e4e204d1a86ec4c0731d2d3f8c331f43117a5ecca","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:45.871292Z","signature_b64":"PmRaatOKSRjPLa63xyRrwmo/zRWIC90ipUEpnlJh1Ewvu7NtXxdgqhByBRwgFM1RnRylwFuKgDcI2dHPqcHbDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"290ab9e5b68a5d4fd97aab8e4e204d1a86ec4c0731d2d3f8c331f43117a5ecca","last_reissued_at":"2026-05-17T23:48:45.870707Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:45.870707Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1804.08782","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":"2026-05-17T23:48:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HQEg+RWOL1GPLjBwnGnhPl5IdpHQ/WwfNxGaKxMjlJekEpn8AkrHPPm9CDB7pGHxzJmOkbTKb3oTfEdHHoDHDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T20:25:42.655064Z"},"content_sha256":"9a806b404c087743b9114908fe4456f490d7e6c1bb23af61f29799e19c91d13b","schema_version":"1.0","event_id":"sha256:9a806b404c087743b9114908fe4456f490d7e6c1bb23af61f29799e19c91d13b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:FEFLTZNWRJOU7WL2VOHE4ICNDK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards an Unsupervised Entrainment Distance in Conversational Speech using Deep Neural Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.SD"],"primary_cat":"eess.AS","authors_text":"Brian Baucom, Md Nasir, Panayiotis Georgiou, Shrikanth Narayanan","submitted_at":"2018-04-23T23:45:30Z","abstract_excerpt":"Entrainment is a known adaptation mechanism that causes interaction participants to adapt or synchronize their acoustic characteristics. Understanding how interlocutors tend to adapt to each other's speaking style through entrainment involves measuring a range of acoustic features and comparing those via multiple signal comparison methods. In this work, we present a turn-level distance measure obtained in an unsupervised manner using a Deep Neural Network (DNN) model, which we call Neural Entrainment Distance (NED). This metric establishes a framework that learns an embedding from the populati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.08782","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":""},"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":"2026-05-17T23:48:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aP+siiK4nIbVZx7f1hw95+tflYGtZqweaDLQ+sQb4E2ndQ00tSVicQd5eHxZ0sKTERua+LfrW1AsWIzjIogbAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T20:25:42.655432Z"},"content_sha256":"a3cefbeab537278b6012f66d5d064d5dd2f173591416d8ede46353a3bea0ab50","schema_version":"1.0","event_id":"sha256:a3cefbeab537278b6012f66d5d064d5dd2f173591416d8ede46353a3bea0ab50"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FEFLTZNWRJOU7WL2VOHE4ICNDK/bundle.json","state_url":"https://pith.science/pith/FEFLTZNWRJOU7WL2VOHE4ICNDK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FEFLTZNWRJOU7WL2VOHE4ICNDK/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":"2026-07-01T20:25:42Z","links":{"resolver":"https://pith.science/pith/FEFLTZNWRJOU7WL2VOHE4ICNDK","bundle":"https://pith.science/pith/FEFLTZNWRJOU7WL2VOHE4ICNDK/bundle.json","state":"https://pith.science/pith/FEFLTZNWRJOU7WL2VOHE4ICNDK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FEFLTZNWRJOU7WL2VOHE4ICNDK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:FEFLTZNWRJOU7WL2VOHE4ICNDK","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":"697e9a801a098bcfe95498dc614d3741027d960d4a4d5024acb15c04014e3c1b","cross_cats_sorted":["cs.CL","cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2018-04-23T23:45:30Z","title_canon_sha256":"a9de1fd605ea30f7afdd4dadc1dae9655d391befd752aef6f096211823023aab"},"schema_version":"1.0","source":{"id":"1804.08782","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.08782","created_at":"2026-05-17T23:48:45Z"},{"alias_kind":"arxiv_version","alias_value":"1804.08782v1","created_at":"2026-05-17T23:48:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.08782","created_at":"2026-05-17T23:48:45Z"},{"alias_kind":"pith_short_12","alias_value":"FEFLTZNWRJOU","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"FEFLTZNWRJOU7WL2","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"FEFLTZNW","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:a3cefbeab537278b6012f66d5d064d5dd2f173591416d8ede46353a3bea0ab50","target":"graph","created_at":"2026-05-17T23:48:45Z","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"},"paper":{"abstract_excerpt":"Entrainment is a known adaptation mechanism that causes interaction participants to adapt or synchronize their acoustic characteristics. Understanding how interlocutors tend to adapt to each other's speaking style through entrainment involves measuring a range of acoustic features and comparing those via multiple signal comparison methods. In this work, we present a turn-level distance measure obtained in an unsupervised manner using a Deep Neural Network (DNN) model, which we call Neural Entrainment Distance (NED). This metric establishes a framework that learns an embedding from the populati","authors_text":"Brian Baucom, Md Nasir, Panayiotis Georgiou, Shrikanth Narayanan","cross_cats":["cs.CL","cs.SD"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2018-04-23T23:45:30Z","title":"Towards an Unsupervised Entrainment Distance in Conversational Speech using Deep Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.08782","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":"sha256:9a806b404c087743b9114908fe4456f490d7e6c1bb23af61f29799e19c91d13b","target":"record","created_at":"2026-05-17T23:48:45Z","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":"697e9a801a098bcfe95498dc614d3741027d960d4a4d5024acb15c04014e3c1b","cross_cats_sorted":["cs.CL","cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2018-04-23T23:45:30Z","title_canon_sha256":"a9de1fd605ea30f7afdd4dadc1dae9655d391befd752aef6f096211823023aab"},"schema_version":"1.0","source":{"id":"1804.08782","kind":"arxiv","version":1}},"canonical_sha256":"290ab9e5b68a5d4fd97aab8e4e204d1a86ec4c0731d2d3f8c331f43117a5ecca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"290ab9e5b68a5d4fd97aab8e4e204d1a86ec4c0731d2d3f8c331f43117a5ecca","first_computed_at":"2026-05-17T23:48:45.870707Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:45.870707Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PmRaatOKSRjPLa63xyRrwmo/zRWIC90ipUEpnlJh1Ewvu7NtXxdgqhByBRwgFM1RnRylwFuKgDcI2dHPqcHbDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:45.871292Z","signed_message":"canonical_sha256_bytes"},"source_id":"1804.08782","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9a806b404c087743b9114908fe4456f490d7e6c1bb23af61f29799e19c91d13b","sha256:a3cefbeab537278b6012f66d5d064d5dd2f173591416d8ede46353a3bea0ab50"],"state_sha256":"deabafc05e2dee777eb307b6b883b0309561542c20f231e409ca6edaf0c66201"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4/MSrALpSaqkzN0Q5vB7ggp9VWGzYvj/TLytdqHuu1Kmp5PbinpJmDyRtEx2VyiDZPvNDj2lg+JoNRtzEVymCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-01T20:25:42.657608Z","bundle_sha256":"a5985af0a0a8695ab1247443f877a9e0cbefff0e027c33404349585e4e74e089"}}