{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:T34D76FAVCENZOU4CI5MCDOFL3","short_pith_number":"pith:T34D76FA","canonical_record":{"source":{"id":"1811.00883","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-11-01T01:21:41Z","cross_cats_sorted":["cs.LG","cs.SD","stat.ML"],"title_canon_sha256":"d5a26b7f8673937b3c7ccf9363cc71b40105de513453c90b69e68ec57ea03c22","abstract_canon_sha256":"6c4f75bc7a426c4e6f39ffacfab0ccaca5aecb466f091d1f8189f9bf22c11e7f"},"schema_version":"1.0"},"canonical_sha256":"9ef83ff8a0a888dcba9c123ac10dc55ef4597032f40c01f09ecb2976615a168c","source":{"kind":"arxiv","id":"1811.00883","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.00883","created_at":"2026-05-18T00:01:41Z"},{"alias_kind":"arxiv_version","alias_value":"1811.00883v1","created_at":"2026-05-18T00:01:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.00883","created_at":"2026-05-18T00:01:41Z"},{"alias_kind":"pith_short_12","alias_value":"T34D76FAVCEN","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"T34D76FAVCENZOU4","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"T34D76FA","created_at":"2026-05-18T12:32:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:T34D76FAVCENZOU4CI5MCDOFL3","target":"record","payload":{"canonical_record":{"source":{"id":"1811.00883","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-11-01T01:21:41Z","cross_cats_sorted":["cs.LG","cs.SD","stat.ML"],"title_canon_sha256":"d5a26b7f8673937b3c7ccf9363cc71b40105de513453c90b69e68ec57ea03c22","abstract_canon_sha256":"6c4f75bc7a426c4e6f39ffacfab0ccaca5aecb466f091d1f8189f9bf22c11e7f"},"schema_version":"1.0"},"canonical_sha256":"9ef83ff8a0a888dcba9c123ac10dc55ef4597032f40c01f09ecb2976615a168c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:01:41.847766Z","signature_b64":"l9uekpPRuAie33QRx+yyHmIAZnSBa71d3bJmOpFhXuYu6xRlWZ4aQ0WcSdYdhy3I1r0S5FIkqXb8E/wGxq9EDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9ef83ff8a0a888dcba9c123ac10dc55ef4597032f40c01f09ecb2976615a168c","last_reissued_at":"2026-05-18T00:01:41.847098Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:01:41.847098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.00883","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":"2026-05-18T00:01:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HYRf5JIh9+CefVHeFMkE+945ozbg8aQ53ty2uDwn+pr3K0XZtSSE57v+SshYSSZbXZq0xIkQB/n2A8wvhlOmBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T07:33:18.735494Z"},"content_sha256":"0bfa27d7405c394709313696830f47c62439bc6b8d1daa26da812d4258b00ab5","schema_version":"1.0","event_id":"sha256:0bfa27d7405c394709313696830f47c62439bc6b8d1daa26da812d4258b00ab5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:T34D76FAVCENZOU4CI5MCDOFL3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Segment Attentive Embedding for Duration Robust Speaker Verification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SD","stat.ML"],"primary_cat":"eess.AS","authors_text":"Bin Liu, Shan Liang, Shuai Nie, Wenju Liu, Yaping Zhang","submitted_at":"2018-11-01T01:21:41Z","abstract_excerpt":"LSTM-based speaker verification usually uses a fixed-length local segment randomly truncated from an utterance to learn the utterance-level speaker embedding, while using the average embedding of all segments of a test utterance to verify the speaker, which results in a critical mismatch between testing and training. This mismatch degrades the performance of speaker verification, especially when the durations of training and testing utterances are very different. To alleviate this issue, we propose the deep segment attentive embedding method to learn the unified speaker embeddings for utteranc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.00883","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":""},"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":"2026-05-18T00:01:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Yhb722r+IkntlhGqjdZKJYNfngACCgQCep5ihQp/8KUEcwf7s5lahtbkCq1Y+wfNXS245CTfxYcyzHME7MyaBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T07:33:18.736135Z"},"content_sha256":"8b6f618c6a0b3b8355d19cb1b12d280bef29f7b64e83503ee2d28c9c54266904","schema_version":"1.0","event_id":"sha256:8b6f618c6a0b3b8355d19cb1b12d280bef29f7b64e83503ee2d28c9c54266904"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/T34D76FAVCENZOU4CI5MCDOFL3/bundle.json","state_url":"https://pith.science/pith/T34D76FAVCENZOU4CI5MCDOFL3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/T34D76FAVCENZOU4CI5MCDOFL3/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":"2026-05-25T07:33:18Z","links":{"resolver":"https://pith.science/pith/T34D76FAVCENZOU4CI5MCDOFL3","bundle":"https://pith.science/pith/T34D76FAVCENZOU4CI5MCDOFL3/bundle.json","state":"https://pith.science/pith/T34D76FAVCENZOU4CI5MCDOFL3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/T34D76FAVCENZOU4CI5MCDOFL3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:T34D76FAVCENZOU4CI5MCDOFL3","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":"6c4f75bc7a426c4e6f39ffacfab0ccaca5aecb466f091d1f8189f9bf22c11e7f","cross_cats_sorted":["cs.LG","cs.SD","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-11-01T01:21:41Z","title_canon_sha256":"d5a26b7f8673937b3c7ccf9363cc71b40105de513453c90b69e68ec57ea03c22"},"schema_version":"1.0","source":{"id":"1811.00883","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.00883","created_at":"2026-05-18T00:01:41Z"},{"alias_kind":"arxiv_version","alias_value":"1811.00883v1","created_at":"2026-05-18T00:01:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.00883","created_at":"2026-05-18T00:01:41Z"},{"alias_kind":"pith_short_12","alias_value":"T34D76FAVCEN","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"T34D76FAVCENZOU4","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"T34D76FA","created_at":"2026-05-18T12:32:53Z"}],"graph_snapshots":[{"event_id":"sha256:8b6f618c6a0b3b8355d19cb1b12d280bef29f7b64e83503ee2d28c9c54266904","target":"graph","created_at":"2026-05-18T00:01:41Z","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"},"paper":{"abstract_excerpt":"LSTM-based speaker verification usually uses a fixed-length local segment randomly truncated from an utterance to learn the utterance-level speaker embedding, while using the average embedding of all segments of a test utterance to verify the speaker, which results in a critical mismatch between testing and training. This mismatch degrades the performance of speaker verification, especially when the durations of training and testing utterances are very different. To alleviate this issue, we propose the deep segment attentive embedding method to learn the unified speaker embeddings for utteranc","authors_text":"Bin Liu, Shan Liang, Shuai Nie, Wenju Liu, Yaping Zhang","cross_cats":["cs.LG","cs.SD","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-11-01T01:21:41Z","title":"Deep Segment Attentive Embedding for Duration Robust Speaker Verification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.00883","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":"sha256:0bfa27d7405c394709313696830f47c62439bc6b8d1daa26da812d4258b00ab5","target":"record","created_at":"2026-05-18T00:01:41Z","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":"6c4f75bc7a426c4e6f39ffacfab0ccaca5aecb466f091d1f8189f9bf22c11e7f","cross_cats_sorted":["cs.LG","cs.SD","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-11-01T01:21:41Z","title_canon_sha256":"d5a26b7f8673937b3c7ccf9363cc71b40105de513453c90b69e68ec57ea03c22"},"schema_version":"1.0","source":{"id":"1811.00883","kind":"arxiv","version":1}},"canonical_sha256":"9ef83ff8a0a888dcba9c123ac10dc55ef4597032f40c01f09ecb2976615a168c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9ef83ff8a0a888dcba9c123ac10dc55ef4597032f40c01f09ecb2976615a168c","first_computed_at":"2026-05-18T00:01:41.847098Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:01:41.847098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"l9uekpPRuAie33QRx+yyHmIAZnSBa71d3bJmOpFhXuYu6xRlWZ4aQ0WcSdYdhy3I1r0S5FIkqXb8E/wGxq9EDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:01:41.847766Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.00883","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0bfa27d7405c394709313696830f47c62439bc6b8d1daa26da812d4258b00ab5","sha256:8b6f618c6a0b3b8355d19cb1b12d280bef29f7b64e83503ee2d28c9c54266904"],"state_sha256":"f314b05e9290614173886ace7f8a3925e2fd14f25562f20a7408f0804f2a9724"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UUa9YkNiFMrHJvtdMaDnsNtv50hJqHO/+MRToxz4vLZ4euLTONuCdvoIkrb5jMklmxrQbSPIR/fZn/t+iPecDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T07:33:18.739098Z","bundle_sha256":"388847ddaee3d704066822d6866fe1c2a796ace94c65cd950ecaf3c4e9c5e2b0"}}