{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:O6DUJDZWWLIBRX2DERY4PJNHL4","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":"7fb105efd30c2ab71d04fd5c054d0167ac2b1ddee3bfdc333f63826eb5dd846f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-23T14:47:25Z","title_canon_sha256":"54502b7f750695f1834221e1d6292e7c002e7d0526f95e6ca5a7d59092283b77"},"schema_version":"1.0","source":{"id":"2407.16537","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.16537","created_at":"2026-07-05T09:16:19Z"},{"alias_kind":"arxiv_version","alias_value":"2407.16537v2","created_at":"2026-07-05T09:16:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.16537","created_at":"2026-07-05T09:16:19Z"},{"alias_kind":"pith_short_12","alias_value":"O6DUJDZWWLIB","created_at":"2026-07-05T09:16:19Z"},{"alias_kind":"pith_short_16","alias_value":"O6DUJDZWWLIBRX2D","created_at":"2026-07-05T09:16:19Z"},{"alias_kind":"pith_short_8","alias_value":"O6DUJDZW","created_at":"2026-07-05T09:16:19Z"}],"graph_snapshots":[{"event_id":"sha256:7094cdc69ac91963c3475f40d0602a2b9be27545aa374c67ca480f762bf8a600","target":"graph","created_at":"2026-07-05T09:16:19Z","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/2407.16537/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A long-standing question in automatic speech recognition research is how to attribute errors to the ability of a model to model the acoustics, versus its ability to leverage higher-order context (lexicon, morphology, syntax, semantics). We validate a novel approach which models error rates as a function of relative textual predictability, and yields a single number, $k$, which measures the effect of textual predictability on the recognizer. We use this method to demonstrate that a Wav2Vec 2.0-based model makes greater stronger use of textual context than a hybrid ASR model, in spite of not usi","authors_text":"Ewan Dunbar, Gerald Penn, Sean Robertson","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-23T14:47:25Z","title":"Quantifying the Role of Textual Predictability in Automatic Speech Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.16537","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":"sha256:61c7ae085ccbc724c4943ccd9cdf2c00ad319e31b924000c533f00966fbec8a0","target":"record","created_at":"2026-07-05T09:16:19Z","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":"7fb105efd30c2ab71d04fd5c054d0167ac2b1ddee3bfdc333f63826eb5dd846f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-23T14:47:25Z","title_canon_sha256":"54502b7f750695f1834221e1d6292e7c002e7d0526f95e6ca5a7d59092283b77"},"schema_version":"1.0","source":{"id":"2407.16537","kind":"arxiv","version":2}},"canonical_sha256":"7787448f36b2d018df432471c7a5a75f3117d59eaf0da4a63883881b6a92eb3e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7787448f36b2d018df432471c7a5a75f3117d59eaf0da4a63883881b6a92eb3e","first_computed_at":"2026-07-05T09:16:19.839139Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:16:19.839139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4C0QMwBhn7CD+KVpTzuxjBA1x3CSdpWhh2TKc2syJfdXWYXPmiePpqRFqhIES7pgwsr+32Qcd2pt3xANJU7fDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:16:19.839633Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.16537","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:61c7ae085ccbc724c4943ccd9cdf2c00ad319e31b924000c533f00966fbec8a0","sha256:7094cdc69ac91963c3475f40d0602a2b9be27545aa374c67ca480f762bf8a600"],"state_sha256":"c504a7b6c99d3dac05236763c49ad09b37e184f272c8badd704671190a46730b"}