{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:Z3GQZDDIXPX423WYEZWS2ECCOP","short_pith_number":"pith:Z3GQZDDI","schema_version":"1.0","canonical_sha256":"cecd0c8c68bbefcd6ed8266d2d104273ebc8d62e726050f485d24f2c6ac35793","source":{"kind":"arxiv","id":"1707.00160","version":3},"attestation_state":"computed","paper":{"title":"An Augmented Lagrangian Method for Piano Transcription using Equal Loudness Thresholding and LSTM-based Decoding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.SD","authors_text":"Mark B. Sandler, Sebastian Ewert","submitted_at":"2017-07-01T14:06:51Z","abstract_excerpt":"A central goal in automatic music transcription is to detect individual note events in music recordings. An important variant is instrument-dependent music transcription where methods can use calibration data for the instruments in use. However, despite the additional information, results rarely exceed an f-measure of 80%. As a potential explanation, the transcription problem can be shown to be badly conditioned and thus relies on appropriate regularization. A recently proposed method employs a mixture of simple, convex regularizers (to stabilize the parameter estimation process) and more comp"},"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":"1707.00160","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-07-01T14:06:51Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"4bcd9d11dab919de3c125b37077436d9be0ac03bde191aaaf6ff1662a711f54e","abstract_canon_sha256":"31fa94d2ab569aff5de135598597fc748b6aeeef95339984ab3533d1c4121c5e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:31:45.000219Z","signature_b64":"oCwrLwAKUU4+gxpHqjDQUqSlSyRuky+z6oNH5ok2097oQSJZZS+lEgFrDQvZvrUd02ALIJD2wseNCyGp7vwlAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cecd0c8c68bbefcd6ed8266d2d104273ebc8d62e726050f485d24f2c6ac35793","last_reissued_at":"2026-05-18T00:31:44.999563Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:31:44.999563Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An Augmented Lagrangian Method for Piano Transcription using Equal Loudness Thresholding and LSTM-based Decoding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.SD","authors_text":"Mark B. Sandler, Sebastian Ewert","submitted_at":"2017-07-01T14:06:51Z","abstract_excerpt":"A central goal in automatic music transcription is to detect individual note events in music recordings. An important variant is instrument-dependent music transcription where methods can use calibration data for the instruments in use. However, despite the additional information, results rarely exceed an f-measure of 80%. As a potential explanation, the transcription problem can be shown to be badly conditioned and thus relies on appropriate regularization. A recently proposed method employs a mixture of simple, convex regularizers (to stabilize the parameter estimation process) and more comp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.00160","kind":"arxiv","version":3},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1707.00160","created_at":"2026-05-18T00:31:44.999678+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.00160v3","created_at":"2026-05-18T00:31:44.999678+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.00160","created_at":"2026-05-18T00:31:44.999678+00:00"},{"alias_kind":"pith_short_12","alias_value":"Z3GQZDDIXPX4","created_at":"2026-05-18T12:31:59.375834+00:00"},{"alias_kind":"pith_short_16","alias_value":"Z3GQZDDIXPX423WY","created_at":"2026-05-18T12:31:59.375834+00:00"},{"alias_kind":"pith_short_8","alias_value":"Z3GQZDDI","created_at":"2026-05-18T12:31:59.375834+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/Z3GQZDDIXPX423WYEZWS2ECCOP","json":"https://pith.science/pith/Z3GQZDDIXPX423WYEZWS2ECCOP.json","graph_json":"https://pith.science/api/pith-number/Z3GQZDDIXPX423WYEZWS2ECCOP/graph.json","events_json":"https://pith.science/api/pith-number/Z3GQZDDIXPX423WYEZWS2ECCOP/events.json","paper":"https://pith.science/paper/Z3GQZDDI"},"agent_actions":{"view_html":"https://pith.science/pith/Z3GQZDDIXPX423WYEZWS2ECCOP","download_json":"https://pith.science/pith/Z3GQZDDIXPX423WYEZWS2ECCOP.json","view_paper":"https://pith.science/paper/Z3GQZDDI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.00160&json=true","fetch_graph":"https://pith.science/api/pith-number/Z3GQZDDIXPX423WYEZWS2ECCOP/graph.json","fetch_events":"https://pith.science/api/pith-number/Z3GQZDDIXPX423WYEZWS2ECCOP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Z3GQZDDIXPX423WYEZWS2ECCOP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Z3GQZDDIXPX423WYEZWS2ECCOP/action/storage_attestation","attest_author":"https://pith.science/pith/Z3GQZDDIXPX423WYEZWS2ECCOP/action/author_attestation","sign_citation":"https://pith.science/pith/Z3GQZDDIXPX423WYEZWS2ECCOP/action/citation_signature","submit_replication":"https://pith.science/pith/Z3GQZDDIXPX423WYEZWS2ECCOP/action/replication_record"}},"created_at":"2026-05-18T00:31:44.999678+00:00","updated_at":"2026-05-18T00:31:44.999678+00:00"}