{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:XAD3NRGXJSO45COIZ77ULXYKOZ","short_pith_number":"pith:XAD3NRGX","schema_version":"1.0","canonical_sha256":"b807b6c4d74c9dce89c8cfff45df0a767df5dc22e37a3db0602a415828bc5849","source":{"kind":"arxiv","id":"2102.09817","version":1},"attestation_state":"computed","paper":{"title":"Unit selection synthesis based data augmentation for fixed phrase speaker verification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.SD","authors_text":"Fei Zhao, Houjun Huang, Shuai Wang, Xu Xiang, Yanmin Qian","submitted_at":"2021-02-19T09:14:23Z","abstract_excerpt":"Data augmentation is commonly used to help build a robust speaker verification system, especially in limited-resource case. However, conventional data augmentation methods usually focus on the diversity of acoustic environment, leaving the lexicon variation neglected. For text dependent speaker verification tasks, it's well-known that preparing training data with the target transcript is the most effectual approach to build a well-performing system, however collecting such data is time-consuming and expensive. In this work, we propose a unit selection synthesis based data augmentation method t"},"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":"2102.09817","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2021-02-19T09:14:23Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"be6bf7f7dc79c76319b8c3e8ce2bc0b498ceff4d4cb286aa1f012f6cf37ef425","abstract_canon_sha256":"debeae72c4cd73de5fc2d6a1b0744bfa44cc222d40824352204b83c9587cbb7a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:16:31.282571Z","signature_b64":"wndjj158Wir1NQ+aL56TQ7wQy2dZEbpb4Uy2JixrwARUA6o7UsPjMJ4UYLuFGshfOeI3ZznjkOIPsBuyIVBQDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b807b6c4d74c9dce89c8cfff45df0a767df5dc22e37a3db0602a415828bc5849","last_reissued_at":"2026-07-05T02:16:31.282092Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:16:31.282092Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Unit selection synthesis based data augmentation for fixed phrase speaker verification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.SD","authors_text":"Fei Zhao, Houjun Huang, Shuai Wang, Xu Xiang, Yanmin Qian","submitted_at":"2021-02-19T09:14:23Z","abstract_excerpt":"Data augmentation is commonly used to help build a robust speaker verification system, especially in limited-resource case. However, conventional data augmentation methods usually focus on the diversity of acoustic environment, leaving the lexicon variation neglected. For text dependent speaker verification tasks, it's well-known that preparing training data with the target transcript is the most effectual approach to build a well-performing system, however collecting such data is time-consuming and expensive. In this work, we propose a unit selection synthesis based data augmentation method t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.09817","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/2102.09817/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":"2102.09817","created_at":"2026-07-05T02:16:31.282149+00:00"},{"alias_kind":"arxiv_version","alias_value":"2102.09817v1","created_at":"2026-07-05T02:16:31.282149+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.09817","created_at":"2026-07-05T02:16:31.282149+00:00"},{"alias_kind":"pith_short_12","alias_value":"XAD3NRGXJSO4","created_at":"2026-07-05T02:16:31.282149+00:00"},{"alias_kind":"pith_short_16","alias_value":"XAD3NRGXJSO45COI","created_at":"2026-07-05T02:16:31.282149+00:00"},{"alias_kind":"pith_short_8","alias_value":"XAD3NRGX","created_at":"2026-07-05T02:16:31.282149+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/XAD3NRGXJSO45COIZ77ULXYKOZ","json":"https://pith.science/pith/XAD3NRGXJSO45COIZ77ULXYKOZ.json","graph_json":"https://pith.science/api/pith-number/XAD3NRGXJSO45COIZ77ULXYKOZ/graph.json","events_json":"https://pith.science/api/pith-number/XAD3NRGXJSO45COIZ77ULXYKOZ/events.json","paper":"https://pith.science/paper/XAD3NRGX"},"agent_actions":{"view_html":"https://pith.science/pith/XAD3NRGXJSO45COIZ77ULXYKOZ","download_json":"https://pith.science/pith/XAD3NRGXJSO45COIZ77ULXYKOZ.json","view_paper":"https://pith.science/paper/XAD3NRGX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2102.09817&json=true","fetch_graph":"https://pith.science/api/pith-number/XAD3NRGXJSO45COIZ77ULXYKOZ/graph.json","fetch_events":"https://pith.science/api/pith-number/XAD3NRGXJSO45COIZ77ULXYKOZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XAD3NRGXJSO45COIZ77ULXYKOZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XAD3NRGXJSO45COIZ77ULXYKOZ/action/storage_attestation","attest_author":"https://pith.science/pith/XAD3NRGXJSO45COIZ77ULXYKOZ/action/author_attestation","sign_citation":"https://pith.science/pith/XAD3NRGXJSO45COIZ77ULXYKOZ/action/citation_signature","submit_replication":"https://pith.science/pith/XAD3NRGXJSO45COIZ77ULXYKOZ/action/replication_record"}},"created_at":"2026-07-05T02:16:31.282149+00:00","updated_at":"2026-07-05T02:16:31.282149+00:00"}