{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:O76VXINKKSHTSP5GNR4DRRWEOT","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":"acc4fe6005da3d0e4aa7ea2cbca6a9aa4064d85444bb988b072ca168e070fe0f","cross_cats_sorted":["cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-28T22:53:54Z","title_canon_sha256":"9cabac2aa51ff792b9cfc7e2c8be4278c2616d8d2582bd9c4f553deeb0008229"},"schema_version":"1.0","source":{"id":"2203.15135","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.15135","created_at":"2026-07-05T04:36:48Z"},{"alias_kind":"arxiv_version","alias_value":"2203.15135v2","created_at":"2026-07-05T04:36:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.15135","created_at":"2026-07-05T04:36:48Z"},{"alias_kind":"pith_short_12","alias_value":"O76VXINKKSHT","created_at":"2026-07-05T04:36:48Z"},{"alias_kind":"pith_short_16","alias_value":"O76VXINKKSHTSP5G","created_at":"2026-07-05T04:36:48Z"},{"alias_kind":"pith_short_8","alias_value":"O76VXINK","created_at":"2026-07-05T04:36:48Z"}],"graph_snapshots":[{"event_id":"sha256:0259ae70c5701ec9f0692d7214a4339966da6bedcbf303089f0e56ba05535a49","target":"graph","created_at":"2026-07-05T04:36:48Z","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/2203.15135/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Filler words such as `uh' or `um' are sounds or words people use to signal they are pausing to think. Finding and removing filler words from recordings is a common and tedious task in media editing. Automatically detecting and classifying filler words could greatly aid in this task, but few studies have been published on this problem to date. A key reason is the absence of a dataset with annotated filler words for model training and evaluation. In this work, we present a novel speech dataset, PodcastFillers, with 35K annotated filler words and 50K annotations of other sounds that commonly occu","authors_text":"Ge Zhu, Juan-Pablo Caceres, Justin Salamon","cross_cats":["cs.SD","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-28T22:53:54Z","title":"Filler Word Detection and Classification: A Dataset and Benchmark"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.15135","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:ca2bb818569b15c52f0981f6b6183b2c122b14b5c3b71bba52665ba1ee4f69d8","target":"record","created_at":"2026-07-05T04:36:48Z","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":"acc4fe6005da3d0e4aa7ea2cbca6a9aa4064d85444bb988b072ca168e070fe0f","cross_cats_sorted":["cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-28T22:53:54Z","title_canon_sha256":"9cabac2aa51ff792b9cfc7e2c8be4278c2616d8d2582bd9c4f553deeb0008229"},"schema_version":"1.0","source":{"id":"2203.15135","kind":"arxiv","version":2}},"canonical_sha256":"77fd5ba1aa548f393fa66c7838c6c474efb80fbf3ac4d1de115d9e3985f72082","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"77fd5ba1aa548f393fa66c7838c6c474efb80fbf3ac4d1de115d9e3985f72082","first_computed_at":"2026-07-05T04:36:48.169478Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:36:48.169478Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NWjdhqsACtwn1dIX2+q7mHrI+lVvOa/HUmRRy0T4jD7dbcPDIW6UnrJ3LbyjL2IlYhnoi38XTHTo9k2GFZiVAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:36:48.169983Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.15135","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ca2bb818569b15c52f0981f6b6183b2c122b14b5c3b71bba52665ba1ee4f69d8","sha256:0259ae70c5701ec9f0692d7214a4339966da6bedcbf303089f0e56ba05535a49"],"state_sha256":"6f7a33ffd684571f24953a3dcee698c0eacf1ec0e3bf2966a47cc9cc070cd671"}