{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:G4BKSPRZLQ7WMYDSJSAU3GFCZP","short_pith_number":"pith:G4BKSPRZ","canonical_record":{"source":{"id":"1912.13307","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-12-31T13:58:58Z","cross_cats_sorted":[],"title_canon_sha256":"c4b368ca39605fd33c5d30be9692d1201695b468b9a196b44109e32e57ca8605","abstract_canon_sha256":"1554a171392bb795de88e0cf8e3d8c95737a40b9c12c7ec6f1c77972008049dc"},"schema_version":"1.0"},"canonical_sha256":"3702a93e395c3f6660724c814d98a2cbfbc85faa3cf449df6e3712ab8544d38e","source":{"kind":"arxiv","id":"1912.13307","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.13307","created_at":"2026-07-05T00:29:07Z"},{"alias_kind":"arxiv_version","alias_value":"1912.13307v1","created_at":"2026-07-05T00:29:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.13307","created_at":"2026-07-05T00:29:07Z"},{"alias_kind":"pith_short_12","alias_value":"G4BKSPRZLQ7W","created_at":"2026-07-05T00:29:07Z"},{"alias_kind":"pith_short_16","alias_value":"G4BKSPRZLQ7WMYDS","created_at":"2026-07-05T00:29:07Z"},{"alias_kind":"pith_short_8","alias_value":"G4BKSPRZ","created_at":"2026-07-05T00:29:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:G4BKSPRZLQ7WMYDSJSAU3GFCZP","target":"record","payload":{"canonical_record":{"source":{"id":"1912.13307","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-12-31T13:58:58Z","cross_cats_sorted":[],"title_canon_sha256":"c4b368ca39605fd33c5d30be9692d1201695b468b9a196b44109e32e57ca8605","abstract_canon_sha256":"1554a171392bb795de88e0cf8e3d8c95737a40b9c12c7ec6f1c77972008049dc"},"schema_version":"1.0"},"canonical_sha256":"3702a93e395c3f6660724c814d98a2cbfbc85faa3cf449df6e3712ab8544d38e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:29:07.728810Z","signature_b64":"FadFhPfvDKfgr8hokRrHt7VuuxyUa5kTc6rDNzSnggYAXp5bqbH18VzD8AAD7qlvpvKySGEiDlSRqDWpU69pDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3702a93e395c3f6660724c814d98a2cbfbc85faa3cf449df6e3712ab8544d38e","last_reissued_at":"2026-07-05T00:29:07.728405Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:29:07.728405Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.13307","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":"2026-07-05T00:29:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YZFqVubuAKgegtJdR46QIjrpG4w0OBXAU9hnbRzSaYyaFKxSqBknWgYttI63bdgnSWNxHu2Shz4V/pPuLYMZDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T18:59:39.578726Z"},"content_sha256":"e7df76db7e1f70e4e45f6b89869c327d3f5f95dead377419363ee8602dd3df7f","schema_version":"1.0","event_id":"sha256:e7df76db7e1f70e4e45f6b89869c327d3f5f95dead377419363ee8602dd3df7f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:G4BKSPRZLQ7WMYDSJSAU3GFCZP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Attention-based gated scaling adaptative acoustic model for ctc-based speech recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.AS","authors_text":"Fenglin Ding, Jun Du, Lirong Dai, Wu Guo","submitted_at":"2019-12-31T13:58:58Z","abstract_excerpt":"In this paper, we propose a novel adaptive technique that uses an attention-based gated scaling (AGS) scheme to improve deep feature learning for connectionist temporal classification (CTC) acoustic modeling. In AGS, the outputs of each hidden layer of the main network are scaled by an auxiliary gate matrix extracted from the lower layer by using attention mechanisms. Furthermore, the auxiliary AGS layer and the main network are jointly trained without requiring second-pass model training or additional speaker information, such as speaker code. On the Mandarin AISHELL-1 datasets, the proposed "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.13307","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/1912.13307/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":"2026-07-05T00:29:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gW9bcQ3nfIGidZW/v5anA49ULArkZvtLT2If2muSwzqRaF5xdX3QIGcG5S7noc0qNE9yC7JrxQa7+k9+UC9WCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T18:59:39.579831Z"},"content_sha256":"3ca409e9a91a3f93defa2d12066c1b7112604eea61e65cf91a3b44f7fd94581a","schema_version":"1.0","event_id":"sha256:3ca409e9a91a3f93defa2d12066c1b7112604eea61e65cf91a3b44f7fd94581a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G4BKSPRZLQ7WMYDSJSAU3GFCZP/bundle.json","state_url":"https://pith.science/pith/G4BKSPRZLQ7WMYDSJSAU3GFCZP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G4BKSPRZLQ7WMYDSJSAU3GFCZP/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":"2026-08-12T18:59:39Z","links":{"resolver":"https://pith.science/pith/G4BKSPRZLQ7WMYDSJSAU3GFCZP","bundle":"https://pith.science/pith/G4BKSPRZLQ7WMYDSJSAU3GFCZP/bundle.json","state":"https://pith.science/pith/G4BKSPRZLQ7WMYDSJSAU3GFCZP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G4BKSPRZLQ7WMYDSJSAU3GFCZP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:G4BKSPRZLQ7WMYDSJSAU3GFCZP","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":"1554a171392bb795de88e0cf8e3d8c95737a40b9c12c7ec6f1c77972008049dc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-12-31T13:58:58Z","title_canon_sha256":"c4b368ca39605fd33c5d30be9692d1201695b468b9a196b44109e32e57ca8605"},"schema_version":"1.0","source":{"id":"1912.13307","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.13307","created_at":"2026-07-05T00:29:07Z"},{"alias_kind":"arxiv_version","alias_value":"1912.13307v1","created_at":"2026-07-05T00:29:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.13307","created_at":"2026-07-05T00:29:07Z"},{"alias_kind":"pith_short_12","alias_value":"G4BKSPRZLQ7W","created_at":"2026-07-05T00:29:07Z"},{"alias_kind":"pith_short_16","alias_value":"G4BKSPRZLQ7WMYDS","created_at":"2026-07-05T00:29:07Z"},{"alias_kind":"pith_short_8","alias_value":"G4BKSPRZ","created_at":"2026-07-05T00:29:07Z"}],"graph_snapshots":[{"event_id":"sha256:3ca409e9a91a3f93defa2d12066c1b7112604eea61e65cf91a3b44f7fd94581a","target":"graph","created_at":"2026-07-05T00:29:07Z","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/1912.13307/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we propose a novel adaptive technique that uses an attention-based gated scaling (AGS) scheme to improve deep feature learning for connectionist temporal classification (CTC) acoustic modeling. In AGS, the outputs of each hidden layer of the main network are scaled by an auxiliary gate matrix extracted from the lower layer by using attention mechanisms. Furthermore, the auxiliary AGS layer and the main network are jointly trained without requiring second-pass model training or additional speaker information, such as speaker code. On the Mandarin AISHELL-1 datasets, the proposed ","authors_text":"Fenglin Ding, Jun Du, Lirong Dai, Wu Guo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-12-31T13:58:58Z","title":"Attention-based gated scaling adaptative acoustic model for ctc-based speech recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.13307","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:e7df76db7e1f70e4e45f6b89869c327d3f5f95dead377419363ee8602dd3df7f","target":"record","created_at":"2026-07-05T00:29:07Z","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":"1554a171392bb795de88e0cf8e3d8c95737a40b9c12c7ec6f1c77972008049dc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-12-31T13:58:58Z","title_canon_sha256":"c4b368ca39605fd33c5d30be9692d1201695b468b9a196b44109e32e57ca8605"},"schema_version":"1.0","source":{"id":"1912.13307","kind":"arxiv","version":1}},"canonical_sha256":"3702a93e395c3f6660724c814d98a2cbfbc85faa3cf449df6e3712ab8544d38e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3702a93e395c3f6660724c814d98a2cbfbc85faa3cf449df6e3712ab8544d38e","first_computed_at":"2026-07-05T00:29:07.728405Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:29:07.728405Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FadFhPfvDKfgr8hokRrHt7VuuxyUa5kTc6rDNzSnggYAXp5bqbH18VzD8AAD7qlvpvKySGEiDlSRqDWpU69pDg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:29:07.728810Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.13307","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e7df76db7e1f70e4e45f6b89869c327d3f5f95dead377419363ee8602dd3df7f","sha256:3ca409e9a91a3f93defa2d12066c1b7112604eea61e65cf91a3b44f7fd94581a"],"state_sha256":"5b265066749cdff7eb801c6ac855a02e3182e61dbf5a98e385e2445c49d93080"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Pqbls125Moo1s2ISRdPMrdFnChBbOE8/F/rmpMgA3pgxxqLtthwHOrIDzxjBSj2uYsAU9n0pFy3QYeyhHeXJCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T18:59:39.587109Z","bundle_sha256":"03f715b7f0597d886343fb9dcf7d188787d28e9428e94f7c82c840d038a211f9"}}