{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:EBVTRTWKMNBJ3Q6Y6RNDDSEIQX","short_pith_number":"pith:EBVTRTWK","canonical_record":{"source":{"id":"2211.06493","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-11-11T22:07:43Z","cross_cats_sorted":["cs.SD","eess.SP"],"title_canon_sha256":"3ccd322fc1cf8427e98277d745bdb94258153ebc17a3ddd4a99ff76ded981811","abstract_canon_sha256":"79a0afc673a54418431dcf7f82ca2d99c4b77d22ae5d1febcaf135db618ef716"},"schema_version":"1.0"},"canonical_sha256":"206b38ceca63429dc3d8f45a31c88885fd25ded692fd4420fd769c7ed4a74350","source":{"kind":"arxiv","id":"2211.06493","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.06493","created_at":"2026-07-05T06:15:43Z"},{"alias_kind":"arxiv_version","alias_value":"2211.06493v2","created_at":"2026-07-05T06:15:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.06493","created_at":"2026-07-05T06:15:43Z"},{"alias_kind":"pith_short_12","alias_value":"EBVTRTWKMNBJ","created_at":"2026-07-05T06:15:43Z"},{"alias_kind":"pith_short_16","alias_value":"EBVTRTWKMNBJ3Q6Y","created_at":"2026-07-05T06:15:43Z"},{"alias_kind":"pith_short_8","alias_value":"EBVTRTWK","created_at":"2026-07-05T06:15:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:EBVTRTWKMNBJ3Q6Y6RNDDSEIQX","target":"record","payload":{"canonical_record":{"source":{"id":"2211.06493","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-11-11T22:07:43Z","cross_cats_sorted":["cs.SD","eess.SP"],"title_canon_sha256":"3ccd322fc1cf8427e98277d745bdb94258153ebc17a3ddd4a99ff76ded981811","abstract_canon_sha256":"79a0afc673a54418431dcf7f82ca2d99c4b77d22ae5d1febcaf135db618ef716"},"schema_version":"1.0"},"canonical_sha256":"206b38ceca63429dc3d8f45a31c88885fd25ded692fd4420fd769c7ed4a74350","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:15:43.777837Z","signature_b64":"mqA25Aeb9iPQrpAcQ9kgxVqk+y8/DPUkCwbBfhESzm9mfc3LacgSqE9l+YtZvtIVtcTOvLUIw4GYUpk6NAZiAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"206b38ceca63429dc3d8f45a31c88885fd25ded692fd4420fd769c7ed4a74350","last_reissued_at":"2026-07-05T06:15:43.777248Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:15:43.777248Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.06493","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:15:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cxma89W4hh/HUVVz4qxqWGliC9LO79lwzmLS9cRPJlUz6JHhVNhqcSLtszIi+UK//iCKehQbpDb+0bGsRejtCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T05:18:21.698782Z"},"content_sha256":"a1231a10a8256845a886764e613d27af7a809002939efb32818c9ce51247eb9b","schema_version":"1.0","event_id":"sha256:a1231a10a8256845a886764e613d27af7a809002939efb32818c9ce51247eb9b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:EBVTRTWKMNBJ3Q6Y6RNDDSEIQX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Handling Trade-Offs in Speech Separation with Sparsely-Gated Mixture of Experts","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SD","eess.SP"],"primary_cat":"eess.AS","authors_text":"Jian Wu, Naoyuki Kanda, Takuya Yoshioka, Xiaofei Wang, Yu Shi, Zhuo Chen","submitted_at":"2022-11-11T22:07:43Z","abstract_excerpt":"Employing a monaural speech separation (SS) model as a front-end for automatic speech recognition (ASR) involves balancing two kinds of trade-offs. First, while a larger model improves the SS performance, it also requires a higher computational cost. Second, an SS model that is more optimized for handling overlapped speech is likely to introduce more processing artifacts in non-overlapped-speech regions. In this paper, we address these trade-offs with a sparsely-gated mixture-of-experts (MoE) architecture. Comprehensive evaluation results obtained using both simulated and real meeting recordin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.06493","kind":"arxiv","version":2},"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/2211.06493/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":"2026-07-05T06:15:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wCXv9Oo0NUCF/3ME3/XROOpa49U0rZ5dcHnwNxs/97JXexg5P7AGxf+CqsIrLWNQC9B0D5J3spZB0AsBS0/uBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T05:18:21.699462Z"},"content_sha256":"9b1f97217a471b5049e11b7b22be971291e9980969ad601382f1c6279b6c88f3","schema_version":"1.0","event_id":"sha256:9b1f97217a471b5049e11b7b22be971291e9980969ad601382f1c6279b6c88f3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EBVTRTWKMNBJ3Q6Y6RNDDSEIQX/bundle.json","state_url":"https://pith.science/pith/EBVTRTWKMNBJ3Q6Y6RNDDSEIQX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EBVTRTWKMNBJ3Q6Y6RNDDSEIQX/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":"2026-08-04T05:18:21Z","links":{"resolver":"https://pith.science/pith/EBVTRTWKMNBJ3Q6Y6RNDDSEIQX","bundle":"https://pith.science/pith/EBVTRTWKMNBJ3Q6Y6RNDDSEIQX/bundle.json","state":"https://pith.science/pith/EBVTRTWKMNBJ3Q6Y6RNDDSEIQX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EBVTRTWKMNBJ3Q6Y6RNDDSEIQX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:EBVTRTWKMNBJ3Q6Y6RNDDSEIQX","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":"79a0afc673a54418431dcf7f82ca2d99c4b77d22ae5d1febcaf135db618ef716","cross_cats_sorted":["cs.SD","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-11-11T22:07:43Z","title_canon_sha256":"3ccd322fc1cf8427e98277d745bdb94258153ebc17a3ddd4a99ff76ded981811"},"schema_version":"1.0","source":{"id":"2211.06493","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.06493","created_at":"2026-07-05T06:15:43Z"},{"alias_kind":"arxiv_version","alias_value":"2211.06493v2","created_at":"2026-07-05T06:15:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.06493","created_at":"2026-07-05T06:15:43Z"},{"alias_kind":"pith_short_12","alias_value":"EBVTRTWKMNBJ","created_at":"2026-07-05T06:15:43Z"},{"alias_kind":"pith_short_16","alias_value":"EBVTRTWKMNBJ3Q6Y","created_at":"2026-07-05T06:15:43Z"},{"alias_kind":"pith_short_8","alias_value":"EBVTRTWK","created_at":"2026-07-05T06:15:43Z"}],"graph_snapshots":[{"event_id":"sha256:9b1f97217a471b5049e11b7b22be971291e9980969ad601382f1c6279b6c88f3","target":"graph","created_at":"2026-07-05T06:15:43Z","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/2211.06493/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Employing a monaural speech separation (SS) model as a front-end for automatic speech recognition (ASR) involves balancing two kinds of trade-offs. First, while a larger model improves the SS performance, it also requires a higher computational cost. Second, an SS model that is more optimized for handling overlapped speech is likely to introduce more processing artifacts in non-overlapped-speech regions. In this paper, we address these trade-offs with a sparsely-gated mixture-of-experts (MoE) architecture. Comprehensive evaluation results obtained using both simulated and real meeting recordin","authors_text":"Jian Wu, Naoyuki Kanda, Takuya Yoshioka, Xiaofei Wang, Yu Shi, Zhuo Chen","cross_cats":["cs.SD","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-11-11T22:07:43Z","title":"Handling Trade-Offs in Speech Separation with Sparsely-Gated Mixture of Experts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.06493","kind":"arxiv","version":2},"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:a1231a10a8256845a886764e613d27af7a809002939efb32818c9ce51247eb9b","target":"record","created_at":"2026-07-05T06:15:43Z","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":"79a0afc673a54418431dcf7f82ca2d99c4b77d22ae5d1febcaf135db618ef716","cross_cats_sorted":["cs.SD","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-11-11T22:07:43Z","title_canon_sha256":"3ccd322fc1cf8427e98277d745bdb94258153ebc17a3ddd4a99ff76ded981811"},"schema_version":"1.0","source":{"id":"2211.06493","kind":"arxiv","version":2}},"canonical_sha256":"206b38ceca63429dc3d8f45a31c88885fd25ded692fd4420fd769c7ed4a74350","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"206b38ceca63429dc3d8f45a31c88885fd25ded692fd4420fd769c7ed4a74350","first_computed_at":"2026-07-05T06:15:43.777248Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:15:43.777248Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mqA25Aeb9iPQrpAcQ9kgxVqk+y8/DPUkCwbBfhESzm9mfc3LacgSqE9l+YtZvtIVtcTOvLUIw4GYUpk6NAZiAg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:15:43.777837Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.06493","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a1231a10a8256845a886764e613d27af7a809002939efb32818c9ce51247eb9b","sha256:9b1f97217a471b5049e11b7b22be971291e9980969ad601382f1c6279b6c88f3"],"state_sha256":"9d7d7ab96fcea5806ec789d18c727040c042ade2fa4cf1298258872bd3357284"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q6SP5Z4iDQGz4P16uembZ3e7VFSyJJ6Me6HjtUDzGKe0lsl5xWEWI81D5Qb/CfHbUy/B6ZtN9sXGKX1IuqEXAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T05:18:21.703169Z","bundle_sha256":"dfd510b433c43fa53c7757448e3ac80b3c2c0351b72c34aee0fc6ed1f66d3fd7"}}