{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:KXI2KH4NSYRMEMMJRF4VGXRA7N","short_pith_number":"pith:KXI2KH4N","schema_version":"1.0","canonical_sha256":"55d1a51f8d9622c231898979535e20fb56dd06fd09472a935561354c671a1433","source":{"kind":"arxiv","id":"2412.06332","version":1},"attestation_state":"computed","paper":{"title":"Not All Errors Are Equal: Investigation of Speech Recognition Errors in Alzheimer's Disease Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG","q-bio.NC"],"primary_cat":"cs.CL","authors_text":"Helen Meng, Jiawen Kang, Jinchao Li, Junan Li, Xixin Wu","submitted_at":"2024-12-09T09:32:20Z","abstract_excerpt":"Automatic Speech Recognition (ASR) plays an important role in speech-based automatic detection of Alzheimer's disease (AD). However, recognition errors could propagate downstream, potentially impacting the detection decisions. Recent studies have revealed a non-linear relationship between word error rates (WER) and AD detection performance, where ASR transcriptions with notable errors could still yield AD detection accuracy equivalent to that based on manual transcriptions. This work presents a series of analyses to explore the effect of ASR transcription errors in BERT-based AD detection syst"},"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":"2412.06332","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-09T09:32:20Z","cross_cats_sorted":["cs.AI","cs.LG","q-bio.NC"],"title_canon_sha256":"f24b2834b7f5f019b1d294d67298f9cbc88920f1f894bd53f9391302556098ce","abstract_canon_sha256":"1a8e3d93119869b2b4d323b9f9178ada78756156a0eb791e95d7689338e65c38"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:46:19.321967Z","signature_b64":"kE7Sy4+2sYyYtTSu0U382/4a+Mn8hJZe5PhPwrgKjcJNs570c43aH1Sy240qq4recpR33X6+DbZUwQAB47m6CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"55d1a51f8d9622c231898979535e20fb56dd06fd09472a935561354c671a1433","last_reissued_at":"2026-07-05T09:46:19.321521Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:46:19.321521Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Not All Errors Are Equal: Investigation of Speech Recognition Errors in Alzheimer's Disease Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG","q-bio.NC"],"primary_cat":"cs.CL","authors_text":"Helen Meng, Jiawen Kang, Jinchao Li, Junan Li, Xixin Wu","submitted_at":"2024-12-09T09:32:20Z","abstract_excerpt":"Automatic Speech Recognition (ASR) plays an important role in speech-based automatic detection of Alzheimer's disease (AD). However, recognition errors could propagate downstream, potentially impacting the detection decisions. Recent studies have revealed a non-linear relationship between word error rates (WER) and AD detection performance, where ASR transcriptions with notable errors could still yield AD detection accuracy equivalent to that based on manual transcriptions. This work presents a series of analyses to explore the effect of ASR transcription errors in BERT-based AD detection syst"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.06332","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/2412.06332/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":"2412.06332","created_at":"2026-07-05T09:46:19.321575+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.06332v1","created_at":"2026-07-05T09:46:19.321575+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.06332","created_at":"2026-07-05T09:46:19.321575+00:00"},{"alias_kind":"pith_short_12","alias_value":"KXI2KH4NSYRM","created_at":"2026-07-05T09:46:19.321575+00:00"},{"alias_kind":"pith_short_16","alias_value":"KXI2KH4NSYRMEMMJ","created_at":"2026-07-05T09:46:19.321575+00:00"},{"alias_kind":"pith_short_8","alias_value":"KXI2KH4N","created_at":"2026-07-05T09:46:19.321575+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2412.06332","citing_title":"Not All Errors Are Equal: Investigation of Speech Recognition Errors in Alzheimer's Disease Detection","ref_index":2,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/KXI2KH4NSYRMEMMJRF4VGXRA7N","json":"https://pith.science/pith/KXI2KH4NSYRMEMMJRF4VGXRA7N.json","graph_json":"https://pith.science/api/pith-number/KXI2KH4NSYRMEMMJRF4VGXRA7N/graph.json","events_json":"https://pith.science/api/pith-number/KXI2KH4NSYRMEMMJRF4VGXRA7N/events.json","paper":"https://pith.science/paper/KXI2KH4N"},"agent_actions":{"view_html":"https://pith.science/pith/KXI2KH4NSYRMEMMJRF4VGXRA7N","download_json":"https://pith.science/pith/KXI2KH4NSYRMEMMJRF4VGXRA7N.json","view_paper":"https://pith.science/paper/KXI2KH4N","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.06332&json=true","fetch_graph":"https://pith.science/api/pith-number/KXI2KH4NSYRMEMMJRF4VGXRA7N/graph.json","fetch_events":"https://pith.science/api/pith-number/KXI2KH4NSYRMEMMJRF4VGXRA7N/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KXI2KH4NSYRMEMMJRF4VGXRA7N/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KXI2KH4NSYRMEMMJRF4VGXRA7N/action/storage_attestation","attest_author":"https://pith.science/pith/KXI2KH4NSYRMEMMJRF4VGXRA7N/action/author_attestation","sign_citation":"https://pith.science/pith/KXI2KH4NSYRMEMMJRF4VGXRA7N/action/citation_signature","submit_replication":"https://pith.science/pith/KXI2KH4NSYRMEMMJRF4VGXRA7N/action/replication_record"}},"created_at":"2026-07-05T09:46:19.321575+00:00","updated_at":"2026-07-05T09:46:19.321575+00:00"}