{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:OOEXUAQP4G35CUSDIENY2ZCXYV","short_pith_number":"pith:OOEXUAQP","schema_version":"1.0","canonical_sha256":"73897a020fe1b7d15243411b8d6457c5695306d32184411155f9d2d49fb147a9","source":{"kind":"arxiv","id":"2210.14252","version":1},"attestation_state":"computed","paper":{"title":"Dynamic Speech Endpoint Detection with Regression Targets","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.SD","authors_text":"Dawei Liang, Edison Thomaz, Hang Su, Jay Mahadeokar, Jiedan Zhu, Mike Seltzer, Shanil Puri, Tarun Singh","submitted_at":"2022-10-25T18:09:42Z","abstract_excerpt":"Interactive voice assistants have been widely used as input interfaces in various scenarios, e.g. on smart homes devices, wearables and on AR devices. Detecting the end of a speech query, i.e. speech end-pointing, is an important task for voice assistants to interact with users. Traditionally, speech end-pointing is based on pure classification methods along with arbitrary binary targets. In this paper, we propose a novel regression-based speech end-pointing model, which enables an end-pointer to adjust its detection behavior based on context of user queries. Specifically, we present a pause m"},"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":"2210.14252","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2022-10-25T18:09:42Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"b1f3de0587958f45d1cd8aa70165297884d08ac190a78c0ed18e0790458fa3f3","abstract_canon_sha256":"629fb73ddc0587ff65508a41a75492e87a0457e6aa58f1242bec1b0f4b65efb4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:10:28.827682Z","signature_b64":"x4r+zLqUqBD8OWgaj92ZZLZRCNLv/l4R9qzR7L6FwGd4bw8uXDcbYSuvp59Qb2tTX2Ky6WSjzhof0o4FNaDLAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"73897a020fe1b7d15243411b8d6457c5695306d32184411155f9d2d49fb147a9","last_reissued_at":"2026-07-05T05:10:28.827160Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:10:28.827160Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dynamic Speech Endpoint Detection with Regression Targets","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.SD","authors_text":"Dawei Liang, Edison Thomaz, Hang Su, Jay Mahadeokar, Jiedan Zhu, Mike Seltzer, Shanil Puri, Tarun Singh","submitted_at":"2022-10-25T18:09:42Z","abstract_excerpt":"Interactive voice assistants have been widely used as input interfaces in various scenarios, e.g. on smart homes devices, wearables and on AR devices. Detecting the end of a speech query, i.e. speech end-pointing, is an important task for voice assistants to interact with users. Traditionally, speech end-pointing is based on pure classification methods along with arbitrary binary targets. In this paper, we propose a novel regression-based speech end-pointing model, which enables an end-pointer to adjust its detection behavior based on context of user queries. Specifically, we present a pause m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.14252","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/2210.14252/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":"2210.14252","created_at":"2026-07-05T05:10:28.827218+00:00"},{"alias_kind":"arxiv_version","alias_value":"2210.14252v1","created_at":"2026-07-05T05:10:28.827218+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.14252","created_at":"2026-07-05T05:10:28.827218+00:00"},{"alias_kind":"pith_short_12","alias_value":"OOEXUAQP4G35","created_at":"2026-07-05T05:10:28.827218+00:00"},{"alias_kind":"pith_short_16","alias_value":"OOEXUAQP4G35CUSD","created_at":"2026-07-05T05:10:28.827218+00:00"},{"alias_kind":"pith_short_8","alias_value":"OOEXUAQP","created_at":"2026-07-05T05:10:28.827218+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/OOEXUAQP4G35CUSDIENY2ZCXYV","json":"https://pith.science/pith/OOEXUAQP4G35CUSDIENY2ZCXYV.json","graph_json":"https://pith.science/api/pith-number/OOEXUAQP4G35CUSDIENY2ZCXYV/graph.json","events_json":"https://pith.science/api/pith-number/OOEXUAQP4G35CUSDIENY2ZCXYV/events.json","paper":"https://pith.science/paper/OOEXUAQP"},"agent_actions":{"view_html":"https://pith.science/pith/OOEXUAQP4G35CUSDIENY2ZCXYV","download_json":"https://pith.science/pith/OOEXUAQP4G35CUSDIENY2ZCXYV.json","view_paper":"https://pith.science/paper/OOEXUAQP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2210.14252&json=true","fetch_graph":"https://pith.science/api/pith-number/OOEXUAQP4G35CUSDIENY2ZCXYV/graph.json","fetch_events":"https://pith.science/api/pith-number/OOEXUAQP4G35CUSDIENY2ZCXYV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OOEXUAQP4G35CUSDIENY2ZCXYV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OOEXUAQP4G35CUSDIENY2ZCXYV/action/storage_attestation","attest_author":"https://pith.science/pith/OOEXUAQP4G35CUSDIENY2ZCXYV/action/author_attestation","sign_citation":"https://pith.science/pith/OOEXUAQP4G35CUSDIENY2ZCXYV/action/citation_signature","submit_replication":"https://pith.science/pith/OOEXUAQP4G35CUSDIENY2ZCXYV/action/replication_record"}},"created_at":"2026-07-05T05:10:28.827218+00:00","updated_at":"2026-07-05T05:10:28.827218+00:00"}