{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:MXJIEVZ4RFV5BJB7ORYZDTXX3Y","short_pith_number":"pith:MXJIEVZ4","canonical_record":{"source":{"id":"2607.09043","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2026-07-10T02:18:02Z","cross_cats_sorted":[],"title_canon_sha256":"7a0292679c61baf2871a99ea8cfac557f3a3bb1fe7febd0c5bf5706b57d765bc","abstract_canon_sha256":"e57bf7ef619d42f387b03ababf6e035b0dd6f41ea4a4bb71beab5184737ced10"},"schema_version":"1.0"},"canonical_sha256":"65d282573c896bd0a43f747191cef7de2fbd585bdd5bef453d342f761a2c7a76","source":{"kind":"arxiv","id":"2607.09043","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.09043","created_at":"2026-07-13T00:17:37Z"},{"alias_kind":"arxiv_version","alias_value":"2607.09043v1","created_at":"2026-07-13T00:17:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.09043","created_at":"2026-07-13T00:17:37Z"},{"alias_kind":"pith_short_12","alias_value":"MXJIEVZ4RFV5","created_at":"2026-07-13T00:17:37Z"},{"alias_kind":"pith_short_16","alias_value":"MXJIEVZ4RFV5BJB7","created_at":"2026-07-13T00:17:37Z"},{"alias_kind":"pith_short_8","alias_value":"MXJIEVZ4","created_at":"2026-07-13T00:17:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:MXJIEVZ4RFV5BJB7ORYZDTXX3Y","target":"record","payload":{"canonical_record":{"source":{"id":"2607.09043","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2026-07-10T02:18:02Z","cross_cats_sorted":[],"title_canon_sha256":"7a0292679c61baf2871a99ea8cfac557f3a3bb1fe7febd0c5bf5706b57d765bc","abstract_canon_sha256":"e57bf7ef619d42f387b03ababf6e035b0dd6f41ea4a4bb71beab5184737ced10"},"schema_version":"1.0"},"canonical_sha256":"65d282573c896bd0a43f747191cef7de2fbd585bdd5bef453d342f761a2c7a76","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-13T00:17:37.257930Z","signature_b64":"RVOtovoH4OmjfkIAw4rhgeYTwdECM4ZESQSwVehNdxkC8KMtLLtA3eJSfkq0+v/z0wpkBUT8tFbZwRXDV1wLAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"65d282573c896bd0a43f747191cef7de2fbd585bdd5bef453d342f761a2c7a76","last_reissued_at":"2026-07-13T00:17:37.256470Z","signature_status":"signed_v1","first_computed_at":"2026-07-13T00:17:37.256470Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.09043","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":"2026-07-13T00:17:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gOgiQNMErBa129BTb67GdItZF2QYoLpsXy1tbkxng8xJwiFd/gklop6aFtWeU6DkWYPG1e4IekYIelAI4ekUDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T06:30:50.212700Z"},"content_sha256":"984a6a21aaccb8e9304d31be8c3b1d5b5774a9114d9d59aa41143e893fa389fb","schema_version":"1.0","event_id":"sha256:984a6a21aaccb8e9304d31be8c3b1d5b5774a9114d9d59aa41143e893fa389fb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:MXJIEVZ4RFV5BJB7ORYZDTXX3Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Technical Report for MERL's Real-TSE Challenge Submission","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.AS","authors_text":"Christoph Boeddeker, Dominik Klement, Gordon Wichern, Jonathan Le Roux, Julius Richter, Kohei Saijo, Yoshiki Masuyama","submitted_at":"2026-07-10T02:18:02Z","abstract_excerpt":"Target speech extraction (TSE) has largely been dominated by neural network-based approaches trained and evaluated on synthetic fully overlapped data. The Real-TSE Challenge aims to advance performance on real-world far-field noisy and reverberant recordings. This technical report describes MERL's submission to the Real-TSE Challenge. Rather than proposing a novel model architecture, we built upon the baseline model and focused primarily on data preparation and cleaning. Our system was trained in four stages, beginning with pre-training on fully overlapped mixtures and simulated multi-talker c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.09043","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/2607.09043/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-13T00:17:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TJ9AZoosgKsolRUfRB5Flv7jF/nmKeevpsBtDUOSyd8P91DBwV/wjQ0V/zy797LwEvNr404erIvytFIS6uz/AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T06:30:50.213200Z"},"content_sha256":"f2273db0e9f7b178bc18218101f98e6136c213d4812712b717eb043b34b6f26f","schema_version":"1.0","event_id":"sha256:f2273db0e9f7b178bc18218101f98e6136c213d4812712b717eb043b34b6f26f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MXJIEVZ4RFV5BJB7ORYZDTXX3Y/bundle.json","state_url":"https://pith.science/pith/MXJIEVZ4RFV5BJB7ORYZDTXX3Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MXJIEVZ4RFV5BJB7ORYZDTXX3Y/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":"2026-08-22T06:30:50Z","links":{"resolver":"https://pith.science/pith/MXJIEVZ4RFV5BJB7ORYZDTXX3Y","bundle":"https://pith.science/pith/MXJIEVZ4RFV5BJB7ORYZDTXX3Y/bundle.json","state":"https://pith.science/pith/MXJIEVZ4RFV5BJB7ORYZDTXX3Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MXJIEVZ4RFV5BJB7ORYZDTXX3Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:MXJIEVZ4RFV5BJB7ORYZDTXX3Y","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":"e57bf7ef619d42f387b03ababf6e035b0dd6f41ea4a4bb71beab5184737ced10","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2026-07-10T02:18:02Z","title_canon_sha256":"7a0292679c61baf2871a99ea8cfac557f3a3bb1fe7febd0c5bf5706b57d765bc"},"schema_version":"1.0","source":{"id":"2607.09043","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.09043","created_at":"2026-07-13T00:17:37Z"},{"alias_kind":"arxiv_version","alias_value":"2607.09043v1","created_at":"2026-07-13T00:17:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.09043","created_at":"2026-07-13T00:17:37Z"},{"alias_kind":"pith_short_12","alias_value":"MXJIEVZ4RFV5","created_at":"2026-07-13T00:17:37Z"},{"alias_kind":"pith_short_16","alias_value":"MXJIEVZ4RFV5BJB7","created_at":"2026-07-13T00:17:37Z"},{"alias_kind":"pith_short_8","alias_value":"MXJIEVZ4","created_at":"2026-07-13T00:17:37Z"}],"graph_snapshots":[{"event_id":"sha256:f2273db0e9f7b178bc18218101f98e6136c213d4812712b717eb043b34b6f26f","target":"graph","created_at":"2026-07-13T00:17:37Z","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/2607.09043/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Target speech extraction (TSE) has largely been dominated by neural network-based approaches trained and evaluated on synthetic fully overlapped data. The Real-TSE Challenge aims to advance performance on real-world far-field noisy and reverberant recordings. This technical report describes MERL's submission to the Real-TSE Challenge. Rather than proposing a novel model architecture, we built upon the baseline model and focused primarily on data preparation and cleaning. Our system was trained in four stages, beginning with pre-training on fully overlapped mixtures and simulated multi-talker c","authors_text":"Christoph Boeddeker, Dominik Klement, Gordon Wichern, Jonathan Le Roux, Julius Richter, Kohei Saijo, Yoshiki Masuyama","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2026-07-10T02:18:02Z","title":"Technical Report for MERL's Real-TSE Challenge Submission"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.09043","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":"sha256:984a6a21aaccb8e9304d31be8c3b1d5b5774a9114d9d59aa41143e893fa389fb","target":"record","created_at":"2026-07-13T00:17:37Z","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":"e57bf7ef619d42f387b03ababf6e035b0dd6f41ea4a4bb71beab5184737ced10","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2026-07-10T02:18:02Z","title_canon_sha256":"7a0292679c61baf2871a99ea8cfac557f3a3bb1fe7febd0c5bf5706b57d765bc"},"schema_version":"1.0","source":{"id":"2607.09043","kind":"arxiv","version":1}},"canonical_sha256":"65d282573c896bd0a43f747191cef7de2fbd585bdd5bef453d342f761a2c7a76","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"65d282573c896bd0a43f747191cef7de2fbd585bdd5bef453d342f761a2c7a76","first_computed_at":"2026-07-13T00:17:37.256470Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-13T00:17:37.256470Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RVOtovoH4OmjfkIAw4rhgeYTwdECM4ZESQSwVehNdxkC8KMtLLtA3eJSfkq0+v/z0wpkBUT8tFbZwRXDV1wLAA==","signature_status":"signed_v1","signed_at":"2026-07-13T00:17:37.257930Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.09043","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:984a6a21aaccb8e9304d31be8c3b1d5b5774a9114d9d59aa41143e893fa389fb","sha256:f2273db0e9f7b178bc18218101f98e6136c213d4812712b717eb043b34b6f26f"],"state_sha256":"ee1067359a514e405c88146f5115be0b619f8b91207c1a120e0312e10e0b9519"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fABVaYBFLpAVuNImdkTZxDU4l6ltGXFHGpVD05R1KDAFQMWjxVv5zcgn//dUI2sl2KTlGaX/S2xG7TJVEoIlBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T06:30:50.218409Z","bundle_sha256":"467e935f3ad71a21b7288d61983aa9ae4d46325fd42b1b758c9903b9ff18a49e"}}