{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:C7JUDVNSC6JMLEEAEX46XSMT6T","short_pith_number":"pith:C7JUDVNS","canonical_record":{"source":{"id":"2012.04494","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-12-08T15:32:21Z","cross_cats_sorted":[],"title_canon_sha256":"d8fdb232e61e49dc1ba529ac5a90d76e17c89e4c0ebc837047f55cf35da0f863","abstract_canon_sha256":"9eb52ff494614d149c06f0db96758842117a63caf404f313550bfdaf3e68c893"},"schema_version":"1.0"},"canonical_sha256":"17d341d5b21792c5908025f9ebc993f4f5f21579ebc1c54522fd9da51ae1b244","source":{"kind":"arxiv","id":"2012.04494","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.04494","created_at":"2026-07-05T02:38:31Z"},{"alias_kind":"arxiv_version","alias_value":"2012.04494v3","created_at":"2026-07-05T02:38:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.04494","created_at":"2026-07-05T02:38:31Z"},{"alias_kind":"pith_short_12","alias_value":"C7JUDVNSC6JM","created_at":"2026-07-05T02:38:31Z"},{"alias_kind":"pith_short_16","alias_value":"C7JUDVNSC6JMLEEA","created_at":"2026-07-05T02:38:31Z"},{"alias_kind":"pith_short_8","alias_value":"C7JUDVNS","created_at":"2026-07-05T02:38:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:C7JUDVNSC6JMLEEAEX46XSMT6T","target":"record","payload":{"canonical_record":{"source":{"id":"2012.04494","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-12-08T15:32:21Z","cross_cats_sorted":[],"title_canon_sha256":"d8fdb232e61e49dc1ba529ac5a90d76e17c89e4c0ebc837047f55cf35da0f863","abstract_canon_sha256":"9eb52ff494614d149c06f0db96758842117a63caf404f313550bfdaf3e68c893"},"schema_version":"1.0"},"canonical_sha256":"17d341d5b21792c5908025f9ebc993f4f5f21579ebc1c54522fd9da51ae1b244","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:38:31.886609Z","signature_b64":"S+q2Cb64vIonuccWv3ZxEvwjppCVQqfGp+HcTJsHdqyF7G6pK324t2M3xsqyB1Zu6bOPcTCpH4rowJKnkpsXDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17d341d5b21792c5908025f9ebc993f4f5f21579ebc1c54522fd9da51ae1b244","last_reissued_at":"2026-07-05T02:38:31.886195Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:38:31.886195Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2012.04494","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:38:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zgu0/b/MgA2lx6cLECiFpXV3LyAbng8GiRIFPdNeQxJAIHQAu+Gve98X+gP3kLw5YgbX/jkw8eq722cPWNUFBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T09:04:46.921232Z"},"content_sha256":"5bc41860840a558590413597ef3e81e2e00fbd86dc2cc5f5a7a2ae55e9322ff0","schema_version":"1.0","event_id":"sha256:5bc41860840a558590413597ef3e81e2e00fbd86dc2cc5f5a7a2ae55e9322ff0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:C7JUDVNSC6JMLEEAEX46XSMT6T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Learning of LF-MMI Trained Time Delay Neural Networks for Speech Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.AS","authors_text":"Helen Meng, Jianwei Yu, Mengzhe Geng, Shansong Liu, Shoukang Hu, Xunying Liu, Xurong Xie, Zi Ye","submitted_at":"2020-12-08T15:32:21Z","abstract_excerpt":"Discriminative training techniques define state-of-the-art performance for automatic speech recognition systems. However, they are inherently prone to overfitting, leading to poor generalization performance when using limited training data. In order to address this issue, this paper presents a full Bayesian framework to account for model uncertainty in sequence discriminative training of factored TDNN acoustic models. Several Bayesian learning based TDNN variant systems are proposed to model the uncertainty over weight parameters and choices of hidden activation functions, or the hidden layer "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.04494","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2012.04494/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":"2026-07-05T02:38:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hvt4DjAaH1+pKzIgmnR3nSsVi5NSPQ+66vkig3bKJtsgWKsSGkDCu1IN6vllaLhoJCePdTSkBW3s82ahIGQrCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T09:04:46.921660Z"},"content_sha256":"affcb520fd555d758887d8e2f87a7f471ab7a3e9ba10279cc0cb0ec86bb429d8","schema_version":"1.0","event_id":"sha256:affcb520fd555d758887d8e2f87a7f471ab7a3e9ba10279cc0cb0ec86bb429d8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C7JUDVNSC6JMLEEAEX46XSMT6T/bundle.json","state_url":"https://pith.science/pith/C7JUDVNSC6JMLEEAEX46XSMT6T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C7JUDVNSC6JMLEEAEX46XSMT6T/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":"2026-07-05T09:04:46Z","links":{"resolver":"https://pith.science/pith/C7JUDVNSC6JMLEEAEX46XSMT6T","bundle":"https://pith.science/pith/C7JUDVNSC6JMLEEAEX46XSMT6T/bundle.json","state":"https://pith.science/pith/C7JUDVNSC6JMLEEAEX46XSMT6T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C7JUDVNSC6JMLEEAEX46XSMT6T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:C7JUDVNSC6JMLEEAEX46XSMT6T","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":"9eb52ff494614d149c06f0db96758842117a63caf404f313550bfdaf3e68c893","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-12-08T15:32:21Z","title_canon_sha256":"d8fdb232e61e49dc1ba529ac5a90d76e17c89e4c0ebc837047f55cf35da0f863"},"schema_version":"1.0","source":{"id":"2012.04494","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.04494","created_at":"2026-07-05T02:38:31Z"},{"alias_kind":"arxiv_version","alias_value":"2012.04494v3","created_at":"2026-07-05T02:38:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.04494","created_at":"2026-07-05T02:38:31Z"},{"alias_kind":"pith_short_12","alias_value":"C7JUDVNSC6JM","created_at":"2026-07-05T02:38:31Z"},{"alias_kind":"pith_short_16","alias_value":"C7JUDVNSC6JMLEEA","created_at":"2026-07-05T02:38:31Z"},{"alias_kind":"pith_short_8","alias_value":"C7JUDVNS","created_at":"2026-07-05T02:38:31Z"}],"graph_snapshots":[{"event_id":"sha256:affcb520fd555d758887d8e2f87a7f471ab7a3e9ba10279cc0cb0ec86bb429d8","target":"graph","created_at":"2026-07-05T02:38:31Z","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/2012.04494/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Discriminative training techniques define state-of-the-art performance for automatic speech recognition systems. However, they are inherently prone to overfitting, leading to poor generalization performance when using limited training data. In order to address this issue, this paper presents a full Bayesian framework to account for model uncertainty in sequence discriminative training of factored TDNN acoustic models. Several Bayesian learning based TDNN variant systems are proposed to model the uncertainty over weight parameters and choices of hidden activation functions, or the hidden layer ","authors_text":"Helen Meng, Jianwei Yu, Mengzhe Geng, Shansong Liu, Shoukang Hu, Xunying Liu, Xurong Xie, Zi Ye","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-12-08T15:32:21Z","title":"Bayesian Learning of LF-MMI Trained Time Delay Neural Networks for Speech Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.04494","kind":"arxiv","version":3},"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":"sha256:5bc41860840a558590413597ef3e81e2e00fbd86dc2cc5f5a7a2ae55e9322ff0","target":"record","created_at":"2026-07-05T02:38:31Z","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":"9eb52ff494614d149c06f0db96758842117a63caf404f313550bfdaf3e68c893","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-12-08T15:32:21Z","title_canon_sha256":"d8fdb232e61e49dc1ba529ac5a90d76e17c89e4c0ebc837047f55cf35da0f863"},"schema_version":"1.0","source":{"id":"2012.04494","kind":"arxiv","version":3}},"canonical_sha256":"17d341d5b21792c5908025f9ebc993f4f5f21579ebc1c54522fd9da51ae1b244","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"17d341d5b21792c5908025f9ebc993f4f5f21579ebc1c54522fd9da51ae1b244","first_computed_at":"2026-07-05T02:38:31.886195Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:38:31.886195Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"S+q2Cb64vIonuccWv3ZxEvwjppCVQqfGp+HcTJsHdqyF7G6pK324t2M3xsqyB1Zu6bOPcTCpH4rowJKnkpsXDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:38:31.886609Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.04494","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5bc41860840a558590413597ef3e81e2e00fbd86dc2cc5f5a7a2ae55e9322ff0","sha256:affcb520fd555d758887d8e2f87a7f471ab7a3e9ba10279cc0cb0ec86bb429d8"],"state_sha256":"ce4139b6787371774d8f19aa086e42c2c920360333fe1b303d8d4cb53d534d67"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QaJ5OjfXA/JStggkQaUWc3cShewayB+UhMZj73I6EU0sFaR7yPA6KSEIz1JPQk3ZeHnxaYl+3K+sDitu3jm9Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T09:04:46.923682Z","bundle_sha256":"6ffe5866e2e9826672d90506f550597d85fcf312dd09c7e6aca6db9ce1578a81"}}