{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:GQYP23CNNCNKXC2LHMA7KEKAWO","short_pith_number":"pith:GQYP23CN","schema_version":"1.0","canonical_sha256":"3430fd6c4d689aab8b4b3b01f51140b3afb1c342a88b25c611dbaf9bc3238867","source":{"kind":"arxiv","id":"2606.17258","version":1},"attestation_state":"computed","paper":{"title":"Single frequency filtering based multi-speaker direction of arrival estimation from stereo recordings","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.AS","authors_text":"Nilesh Madhu, Sudarsana Reddy Kadiri, Suryakanth V Gangashetty, Sushmita Thakallapalli","submitted_at":"2026-06-15T20:07:07Z","abstract_excerpt":"Robust direction-of-arrival (DoA) estimation from noisy and reverberant microphone signals remains challenging. Conventional estimators such as generalized cross-correlation (GCC) and its variants operate in the short-time Fourier transform (STFT) domain, where spectral features primarily reflect vocal-tract characteristics. Recent single frequency filtering (SFF)-based estimators instead use a time-frequency representation that provides high spectral resolution of harmonics along with high temporal resolution of excitation-source events, such as epoch-like impulses. Since excitation-source fe"},"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":"2606.17258","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.AS","submitted_at":"2026-06-15T20:07:07Z","cross_cats_sorted":[],"title_canon_sha256":"91079764cb33a9c58f0a6154de3ac36ab39e38deac4847eb79fa7ddb9291bb35","abstract_canon_sha256":"ccb069647f1149305232f92b591da130730ebe853253d8ac1c065555e41aa53e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:10:07.172029Z","signature_b64":"qDwn2E6dtYHjQ5ZoOtMe7CkisdiAfOJcrV34rGfu8QuSSAHfNmwhNbuP5gypo1lfuvdj5d5p7cedWJhs6AYmDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3430fd6c4d689aab8b4b3b01f51140b3afb1c342a88b25c611dbaf9bc3238867","last_reissued_at":"2026-06-19T16:10:07.171662Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:10:07.171662Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Single frequency filtering based multi-speaker direction of arrival estimation from stereo recordings","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.AS","authors_text":"Nilesh Madhu, Sudarsana Reddy Kadiri, Suryakanth V Gangashetty, Sushmita Thakallapalli","submitted_at":"2026-06-15T20:07:07Z","abstract_excerpt":"Robust direction-of-arrival (DoA) estimation from noisy and reverberant microphone signals remains challenging. Conventional estimators such as generalized cross-correlation (GCC) and its variants operate in the short-time Fourier transform (STFT) domain, where spectral features primarily reflect vocal-tract characteristics. Recent single frequency filtering (SFF)-based estimators instead use a time-frequency representation that provides high spectral resolution of harmonics along with high temporal resolution of excitation-source events, such as epoch-like impulses. Since excitation-source fe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.17258","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/2606.17258/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":"2606.17258","created_at":"2026-06-19T16:10:07.171727+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.17258v1","created_at":"2026-06-19T16:10:07.171727+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.17258","created_at":"2026-06-19T16:10:07.171727+00:00"},{"alias_kind":"pith_short_12","alias_value":"GQYP23CNNCNK","created_at":"2026-06-19T16:10:07.171727+00:00"},{"alias_kind":"pith_short_16","alias_value":"GQYP23CNNCNKXC2L","created_at":"2026-06-19T16:10:07.171727+00:00"},{"alias_kind":"pith_short_8","alias_value":"GQYP23CN","created_at":"2026-06-19T16:10:07.171727+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/GQYP23CNNCNKXC2LHMA7KEKAWO","json":"https://pith.science/pith/GQYP23CNNCNKXC2LHMA7KEKAWO.json","graph_json":"https://pith.science/api/pith-number/GQYP23CNNCNKXC2LHMA7KEKAWO/graph.json","events_json":"https://pith.science/api/pith-number/GQYP23CNNCNKXC2LHMA7KEKAWO/events.json","paper":"https://pith.science/paper/GQYP23CN"},"agent_actions":{"view_html":"https://pith.science/pith/GQYP23CNNCNKXC2LHMA7KEKAWO","download_json":"https://pith.science/pith/GQYP23CNNCNKXC2LHMA7KEKAWO.json","view_paper":"https://pith.science/paper/GQYP23CN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.17258&json=true","fetch_graph":"https://pith.science/api/pith-number/GQYP23CNNCNKXC2LHMA7KEKAWO/graph.json","fetch_events":"https://pith.science/api/pith-number/GQYP23CNNCNKXC2LHMA7KEKAWO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GQYP23CNNCNKXC2LHMA7KEKAWO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GQYP23CNNCNKXC2LHMA7KEKAWO/action/storage_attestation","attest_author":"https://pith.science/pith/GQYP23CNNCNKXC2LHMA7KEKAWO/action/author_attestation","sign_citation":"https://pith.science/pith/GQYP23CNNCNKXC2LHMA7KEKAWO/action/citation_signature","submit_replication":"https://pith.science/pith/GQYP23CNNCNKXC2LHMA7KEKAWO/action/replication_record"}},"created_at":"2026-06-19T16:10:07.171727+00:00","updated_at":"2026-06-19T16:10:07.171727+00:00"}