{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:EGW74WX73OC7D3ZSYSHI74MY4T","short_pith_number":"pith:EGW74WX7","canonical_record":{"source":{"id":"2110.01857","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-10-05T07:45:55Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"e18a732968353d32c60c318bccc3263d4e440538cac1029517e94f892565a223","abstract_canon_sha256":"5d6a458a869fc6f712976fcf5cdcd2a9e44466a29048bf98c1894efa017b941c"},"schema_version":"1.0"},"canonical_sha256":"21adfe5affdb85f1ef32c48e8ff198e4cecdb6e5b34ba3fa483266032b8122c1","source":{"kind":"arxiv","id":"2110.01857","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.01857","created_at":"2026-07-05T03:20:07Z"},{"alias_kind":"arxiv_version","alias_value":"2110.01857v1","created_at":"2026-07-05T03:20:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.01857","created_at":"2026-07-05T03:20:07Z"},{"alias_kind":"pith_short_12","alias_value":"EGW74WX73OC7","created_at":"2026-07-05T03:20:07Z"},{"alias_kind":"pith_short_16","alias_value":"EGW74WX73OC7D3ZS","created_at":"2026-07-05T03:20:07Z"},{"alias_kind":"pith_short_8","alias_value":"EGW74WX7","created_at":"2026-07-05T03:20:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:EGW74WX73OC7D3ZSYSHI74MY4T","target":"record","payload":{"canonical_record":{"source":{"id":"2110.01857","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-10-05T07:45:55Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"e18a732968353d32c60c318bccc3263d4e440538cac1029517e94f892565a223","abstract_canon_sha256":"5d6a458a869fc6f712976fcf5cdcd2a9e44466a29048bf98c1894efa017b941c"},"schema_version":"1.0"},"canonical_sha256":"21adfe5affdb85f1ef32c48e8ff198e4cecdb6e5b34ba3fa483266032b8122c1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:20:07.039587Z","signature_b64":"5lbjwBYn2uUfklvFaYwok7JAjCx4vadnsXMhtfspF24+uGpXs3tacVYMjm7OetfrVBmY/2mA9BWeDH3szxAkAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"21adfe5affdb85f1ef32c48e8ff198e4cecdb6e5b34ba3fa483266032b8122c1","last_reissued_at":"2026-07-05T03:20:07.039119Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:20:07.039119Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.01857","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":"2026-07-05T03:20:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KLransuqn95F1gPp3QqvxfHhKsOaSFQ0/Pz7JTJ/BrL2WAfEfJXd15ovL6ro9779aX51NMYVUb47gUIahb4dAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T18:36:29.859479Z"},"content_sha256":"5223b806293f7b5c1e89e891ddc7eb759cf108ce41e588fcc6e5360fddcc86f2","schema_version":"1.0","event_id":"sha256:5223b806293f7b5c1e89e891ddc7eb759cf108ce41e588fcc6e5360fddcc86f2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:EGW74WX73OC7D3ZSYSHI74MY4T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ASR Rescoring and Confidence Estimation with ELECTRA","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.CL","authors_text":"Hayato Futami, Hirofumi Inaguma, Masato Mimura, Shinsuke Sakai, Tatsuya Kawahara","submitted_at":"2021-10-05T07:45:55Z","abstract_excerpt":"In automatic speech recognition (ASR) rescoring, the hypothesis with the fewest errors should be selected from the n-best list using a language model (LM). However, LMs are usually trained to maximize the likelihood of correct word sequences, not to detect ASR errors. We propose an ASR rescoring method for directly detecting errors with ELECTRA, which is originally a pre-training method for NLP tasks. ELECTRA is pre-trained to predict whether each word is replaced by BERT or not, which can simulate ASR error detection on large text corpora. To make this pre-training closer to ASR error detecti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.01857","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/2110.01857/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":"2026-07-05T03:20:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N9bVpstGVcxAh0k4NUHre6LNM1wt3Fvmjfrlubp7rAUCoLq12/KotkqyEYR7BKrXt5zRrra19KI+wmXlutXFCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T18:36:29.860390Z"},"content_sha256":"9d5fec1a320c43007e83838efb9e1f3a45513b0ed91203e6bf522204cb89edb5","schema_version":"1.0","event_id":"sha256:9d5fec1a320c43007e83838efb9e1f3a45513b0ed91203e6bf522204cb89edb5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EGW74WX73OC7D3ZSYSHI74MY4T/bundle.json","state_url":"https://pith.science/pith/EGW74WX73OC7D3ZSYSHI74MY4T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EGW74WX73OC7D3ZSYSHI74MY4T/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":"2026-08-08T18:36:29Z","links":{"resolver":"https://pith.science/pith/EGW74WX73OC7D3ZSYSHI74MY4T","bundle":"https://pith.science/pith/EGW74WX73OC7D3ZSYSHI74MY4T/bundle.json","state":"https://pith.science/pith/EGW74WX73OC7D3ZSYSHI74MY4T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EGW74WX73OC7D3ZSYSHI74MY4T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:EGW74WX73OC7D3ZSYSHI74MY4T","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":"5d6a458a869fc6f712976fcf5cdcd2a9e44466a29048bf98c1894efa017b941c","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-10-05T07:45:55Z","title_canon_sha256":"e18a732968353d32c60c318bccc3263d4e440538cac1029517e94f892565a223"},"schema_version":"1.0","source":{"id":"2110.01857","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.01857","created_at":"2026-07-05T03:20:07Z"},{"alias_kind":"arxiv_version","alias_value":"2110.01857v1","created_at":"2026-07-05T03:20:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.01857","created_at":"2026-07-05T03:20:07Z"},{"alias_kind":"pith_short_12","alias_value":"EGW74WX73OC7","created_at":"2026-07-05T03:20:07Z"},{"alias_kind":"pith_short_16","alias_value":"EGW74WX73OC7D3ZS","created_at":"2026-07-05T03:20:07Z"},{"alias_kind":"pith_short_8","alias_value":"EGW74WX7","created_at":"2026-07-05T03:20:07Z"}],"graph_snapshots":[{"event_id":"sha256:9d5fec1a320c43007e83838efb9e1f3a45513b0ed91203e6bf522204cb89edb5","target":"graph","created_at":"2026-07-05T03:20:07Z","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/2110.01857/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In automatic speech recognition (ASR) rescoring, the hypothesis with the fewest errors should be selected from the n-best list using a language model (LM). However, LMs are usually trained to maximize the likelihood of correct word sequences, not to detect ASR errors. We propose an ASR rescoring method for directly detecting errors with ELECTRA, which is originally a pre-training method for NLP tasks. ELECTRA is pre-trained to predict whether each word is replaced by BERT or not, which can simulate ASR error detection on large text corpora. To make this pre-training closer to ASR error detecti","authors_text":"Hayato Futami, Hirofumi Inaguma, Masato Mimura, Shinsuke Sakai, Tatsuya Kawahara","cross_cats":["eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-10-05T07:45:55Z","title":"ASR Rescoring and Confidence Estimation with ELECTRA"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.01857","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":"sha256:5223b806293f7b5c1e89e891ddc7eb759cf108ce41e588fcc6e5360fddcc86f2","target":"record","created_at":"2026-07-05T03:20:07Z","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":"5d6a458a869fc6f712976fcf5cdcd2a9e44466a29048bf98c1894efa017b941c","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-10-05T07:45:55Z","title_canon_sha256":"e18a732968353d32c60c318bccc3263d4e440538cac1029517e94f892565a223"},"schema_version":"1.0","source":{"id":"2110.01857","kind":"arxiv","version":1}},"canonical_sha256":"21adfe5affdb85f1ef32c48e8ff198e4cecdb6e5b34ba3fa483266032b8122c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"21adfe5affdb85f1ef32c48e8ff198e4cecdb6e5b34ba3fa483266032b8122c1","first_computed_at":"2026-07-05T03:20:07.039119Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:20:07.039119Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5lbjwBYn2uUfklvFaYwok7JAjCx4vadnsXMhtfspF24+uGpXs3tacVYMjm7OetfrVBmY/2mA9BWeDH3szxAkAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:20:07.039587Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.01857","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5223b806293f7b5c1e89e891ddc7eb759cf108ce41e588fcc6e5360fddcc86f2","sha256:9d5fec1a320c43007e83838efb9e1f3a45513b0ed91203e6bf522204cb89edb5"],"state_sha256":"a784a8ad2bb717c55880e7fd817faf370b00a5ca633e974f1a17c8eb8fd0ae09"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rNPttD/52LLAKTc//nSObdEfEjZkTT7aXN/GQ1hGfvwxDybs5qeMGPpPHx0vuhFBn+9u6egThJAntACufGeKDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T18:36:29.867087Z","bundle_sha256":"e151a0d6d4ec0f3234ed707503d7674bb756838531dceb6582ed2d91bdc85897"}}