{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:WM4POG7ERLDORTLH6WBERBU54R","short_pith_number":"pith:WM4POG7E","canonical_record":{"source":{"id":"2110.10812","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2021-10-20T22:39:35Z","cross_cats_sorted":["cs.LG","cs.SD","eess.SP"],"title_canon_sha256":"8f1c36775d18f30d52668a87fa5d660eb432fb9409d93203546fbe3573372cfa","abstract_canon_sha256":"5adb23f8221dfe21e0bfee54fa219811da9cb12b3df1a8ef80ae7b9e98e3ff11"},"schema_version":"1.0"},"canonical_sha256":"b338f71be48ac6e8cd67f58248869de4447ef428c008e1e6c59168cc6f32d1b8","source":{"kind":"arxiv","id":"2110.10812","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.10812","created_at":"2026-07-05T03:24:32Z"},{"alias_kind":"arxiv_version","alias_value":"2110.10812v1","created_at":"2026-07-05T03:24:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.10812","created_at":"2026-07-05T03:24:32Z"},{"alias_kind":"pith_short_12","alias_value":"WM4POG7ERLDO","created_at":"2026-07-05T03:24:32Z"},{"alias_kind":"pith_short_16","alias_value":"WM4POG7ERLDORTLH","created_at":"2026-07-05T03:24:32Z"},{"alias_kind":"pith_short_8","alias_value":"WM4POG7E","created_at":"2026-07-05T03:24:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:WM4POG7ERLDORTLH6WBERBU54R","target":"record","payload":{"canonical_record":{"source":{"id":"2110.10812","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2021-10-20T22:39:35Z","cross_cats_sorted":["cs.LG","cs.SD","eess.SP"],"title_canon_sha256":"8f1c36775d18f30d52668a87fa5d660eb432fb9409d93203546fbe3573372cfa","abstract_canon_sha256":"5adb23f8221dfe21e0bfee54fa219811da9cb12b3df1a8ef80ae7b9e98e3ff11"},"schema_version":"1.0"},"canonical_sha256":"b338f71be48ac6e8cd67f58248869de4447ef428c008e1e6c59168cc6f32d1b8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:24:32.751831Z","signature_b64":"FTCeJMvq/5KoJZyb7SIg39GGTs3HaivDCNTkP7yoqGsdyO5frE2p9rXidYJkG93QDKlJ9ZhqKsfxESRgW3/oAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b338f71be48ac6e8cd67f58248869de4447ef428c008e1e6c59168cc6f32d1b8","last_reissued_at":"2026-07-05T03:24:32.751309Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:24:32.751309Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.10812","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":"2026-07-05T03:24:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7EcWssHMp49ZnGIhrhmnVnb80z92ng1cJrJApFMbELknkeH17UHz5P5sIDJYe4ea/q75o9XvWSJP0ZXT7kvgDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T16:57:46.853967Z"},"content_sha256":"68cfc336439eab35f8ee6686123fc186f07604d36490efad1ed76bed80eab490","schema_version":"1.0","event_id":"sha256:68cfc336439eab35f8ee6686123fc186f07604d36490efad1ed76bed80eab490"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:WM4POG7ERLDORTLH6WBERBU54R","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"REAL-M: Towards Speech Separation on Real Mixtures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SD","eess.SP"],"primary_cat":"eess.AS","authors_text":"Cem Subakan, Fran\\c{c}ois Grondin, Mirco Ravanelli, Samuele Cornell","submitted_at":"2021-10-20T22:39:35Z","abstract_excerpt":"In recent years, deep learning based source separation has achieved impressive results. Most studies, however, still evaluate separation models on synthetic datasets, while the performance of state-of-the-art techniques on in-the-wild speech data remains an open question. This paper contributes to fill this gap in two ways. First, we release the REAL-M dataset, a crowd-sourced corpus of real-life mixtures. Secondly, we address the problem of performance evaluation of real-life mixtures, where the ground truth is not available. We bypass this issue by carefully designing a blind Scale-Invariant"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.10812","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/2110.10812/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":"2026-07-05T03:24:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WMBWJuOuU1Rf+Oo0GB6tjhLwbSYJ5uTvZuk1nSWlbmrwN7pBiDwgTsaFp1BninlpyjY4BD4Jh2YVYYK3QUgEAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T16:57:46.854358Z"},"content_sha256":"ac03a223b788d31fcafe63c5a7137c076c15d58a1b5b89c53b4b1bd103cfbf19","schema_version":"1.0","event_id":"sha256:ac03a223b788d31fcafe63c5a7137c076c15d58a1b5b89c53b4b1bd103cfbf19"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WM4POG7ERLDORTLH6WBERBU54R/bundle.json","state_url":"https://pith.science/pith/WM4POG7ERLDORTLH6WBERBU54R/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WM4POG7ERLDORTLH6WBERBU54R/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":"2026-07-06T16:57:46Z","links":{"resolver":"https://pith.science/pith/WM4POG7ERLDORTLH6WBERBU54R","bundle":"https://pith.science/pith/WM4POG7ERLDORTLH6WBERBU54R/bundle.json","state":"https://pith.science/pith/WM4POG7ERLDORTLH6WBERBU54R/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WM4POG7ERLDORTLH6WBERBU54R/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:WM4POG7ERLDORTLH6WBERBU54R","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":"5adb23f8221dfe21e0bfee54fa219811da9cb12b3df1a8ef80ae7b9e98e3ff11","cross_cats_sorted":["cs.LG","cs.SD","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2021-10-20T22:39:35Z","title_canon_sha256":"8f1c36775d18f30d52668a87fa5d660eb432fb9409d93203546fbe3573372cfa"},"schema_version":"1.0","source":{"id":"2110.10812","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.10812","created_at":"2026-07-05T03:24:32Z"},{"alias_kind":"arxiv_version","alias_value":"2110.10812v1","created_at":"2026-07-05T03:24:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.10812","created_at":"2026-07-05T03:24:32Z"},{"alias_kind":"pith_short_12","alias_value":"WM4POG7ERLDO","created_at":"2026-07-05T03:24:32Z"},{"alias_kind":"pith_short_16","alias_value":"WM4POG7ERLDORTLH","created_at":"2026-07-05T03:24:32Z"},{"alias_kind":"pith_short_8","alias_value":"WM4POG7E","created_at":"2026-07-05T03:24:32Z"}],"graph_snapshots":[{"event_id":"sha256:ac03a223b788d31fcafe63c5a7137c076c15d58a1b5b89c53b4b1bd103cfbf19","target":"graph","created_at":"2026-07-05T03:24:32Z","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/2110.10812/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, deep learning based source separation has achieved impressive results. Most studies, however, still evaluate separation models on synthetic datasets, while the performance of state-of-the-art techniques on in-the-wild speech data remains an open question. This paper contributes to fill this gap in two ways. First, we release the REAL-M dataset, a crowd-sourced corpus of real-life mixtures. Secondly, we address the problem of performance evaluation of real-life mixtures, where the ground truth is not available. We bypass this issue by carefully designing a blind Scale-Invariant","authors_text":"Cem Subakan, Fran\\c{c}ois Grondin, Mirco Ravanelli, Samuele Cornell","cross_cats":["cs.LG","cs.SD","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2021-10-20T22:39:35Z","title":"REAL-M: Towards Speech Separation on Real Mixtures"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.10812","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":"sha256:68cfc336439eab35f8ee6686123fc186f07604d36490efad1ed76bed80eab490","target":"record","created_at":"2026-07-05T03:24:32Z","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":"5adb23f8221dfe21e0bfee54fa219811da9cb12b3df1a8ef80ae7b9e98e3ff11","cross_cats_sorted":["cs.LG","cs.SD","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2021-10-20T22:39:35Z","title_canon_sha256":"8f1c36775d18f30d52668a87fa5d660eb432fb9409d93203546fbe3573372cfa"},"schema_version":"1.0","source":{"id":"2110.10812","kind":"arxiv","version":1}},"canonical_sha256":"b338f71be48ac6e8cd67f58248869de4447ef428c008e1e6c59168cc6f32d1b8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b338f71be48ac6e8cd67f58248869de4447ef428c008e1e6c59168cc6f32d1b8","first_computed_at":"2026-07-05T03:24:32.751309Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:24:32.751309Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FTCeJMvq/5KoJZyb7SIg39GGTs3HaivDCNTkP7yoqGsdyO5frE2p9rXidYJkG93QDKlJ9ZhqKsfxESRgW3/oAg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:24:32.751831Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.10812","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:68cfc336439eab35f8ee6686123fc186f07604d36490efad1ed76bed80eab490","sha256:ac03a223b788d31fcafe63c5a7137c076c15d58a1b5b89c53b4b1bd103cfbf19"],"state_sha256":"2d1d49305e9d1a3c8b3dfb97a6fe773b63db3b722c46cbc63a93cbb567640ce0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xIO1/spQikXuyX3teqz+wxI3djAeVBmaHYxObry43+lGKUtVLq4nryw7SZSr7MgGaiG/eDGt+etAPtUTsMmQAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T16:57:46.856379Z","bundle_sha256":"c67b97b42d4b63e40df7de5cccac155e189b21d33d1d1cc75a996ee70d27ceb8"}}