{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:THJJBDIQ53VLVLRLZK5ZFSH2UF","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":"db9ed4fe9c83da7d20306084e11c2415c287a2c5f576b07ae99ccaac39ab3623","cross_cats_sorted":["cs.CL","cs.LG","cs.SD","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-04-07T08:35:05Z","title_canon_sha256":"e3a2f84658c517753d8eee78aa8f802621f6a174af4b9dc5649cef12dcda3dc4"},"schema_version":"1.0","source":{"id":"2004.03194","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.03194","created_at":"2026-07-05T01:49:36Z"},{"alias_kind":"arxiv_version","alias_value":"2004.03194v4","created_at":"2026-07-05T01:49:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.03194","created_at":"2026-07-05T01:49:36Z"},{"alias_kind":"pith_short_12","alias_value":"THJJBDIQ53VL","created_at":"2026-07-05T01:49:36Z"},{"alias_kind":"pith_short_16","alias_value":"THJJBDIQ53VLVLRL","created_at":"2026-07-05T01:49:36Z"},{"alias_kind":"pith_short_8","alias_value":"THJJBDIQ","created_at":"2026-07-05T01:49:36Z"}],"graph_snapshots":[{"event_id":"sha256:21a47e98da846f105a86aa56be6d20b5bdb80748fa5f4c4b4a0ecb0742a61e18","target":"graph","created_at":"2026-07-05T01:49:36Z","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/2004.03194/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Currently, the most widely used approach for speaker verification is the deep speaker embedding learning. In this approach, we obtain a speaker embedding vector by pooling single-scale features that are extracted from the last layer of a speaker feature extractor. Multi-scale aggregation (MSA), which utilizes multi-scale features from different layers of the feature extractor, has recently been introduced and shows superior performance for variable-duration utterances. To increase the robustness dealing with utterances of arbitrary duration, this paper improves the MSA by using a feature pyram","authors_text":"Hoirin Kim, Myunghun Jung, Seong Min Kye, Yeunju Choi, Youngmoon Jung","cross_cats":["cs.CL","cs.LG","cs.SD","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-04-07T08:35:05Z","title":"Improving Multi-Scale Aggregation Using Feature Pyramid Module for Robust Speaker Verification of Variable-Duration Utterances"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.03194","kind":"arxiv","version":4},"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":"sha256:3d91927746f1c4dd561cd0fecbf4cfb9dd6a5cc7a9b4832f979a80e7a4d4db65","target":"record","created_at":"2026-07-05T01:49:36Z","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":"db9ed4fe9c83da7d20306084e11c2415c287a2c5f576b07ae99ccaac39ab3623","cross_cats_sorted":["cs.CL","cs.LG","cs.SD","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-04-07T08:35:05Z","title_canon_sha256":"e3a2f84658c517753d8eee78aa8f802621f6a174af4b9dc5649cef12dcda3dc4"},"schema_version":"1.0","source":{"id":"2004.03194","kind":"arxiv","version":4}},"canonical_sha256":"99d2908d10eeeabaae2bcabb92c8faa14e52e30fd438db9ba1d7f1e10390bf56","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"99d2908d10eeeabaae2bcabb92c8faa14e52e30fd438db9ba1d7f1e10390bf56","first_computed_at":"2026-07-05T01:49:36.449909Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:49:36.449909Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+z6vEwPz563UbIwOVitmmJ6hDq21BK+N5iXjZxwGtZVdDoNH/RDUBqycERFifIZFm2NLVzPkuDv4x7pgmrEZAA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:49:36.450350Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.03194","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d91927746f1c4dd561cd0fecbf4cfb9dd6a5cc7a9b4832f979a80e7a4d4db65","sha256:21a47e98da846f105a86aa56be6d20b5bdb80748fa5f4c4b4a0ecb0742a61e18"],"state_sha256":"1550130ff1555bf71ea5ccb7b529e5e4b796b81ecc6f6ded7dc3d0ff89db5c71"}