{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:TPAIHE4AOLMTNM7W3NJ6KVDPDU","short_pith_number":"pith:TPAIHE4A","canonical_record":{"source":{"id":"2002.02562","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-02-07T00:04:04Z","cross_cats_sorted":["cs.CL","cs.SD"],"title_canon_sha256":"9362875260d778da20f17d673bbae44fced2687df3faef51a74ca681422bba7d","abstract_canon_sha256":"baf50dbebddf980c2018d6e5a831e4f43bce942d2f631fe53c6b54a4eb319442"},"schema_version":"1.0"},"canonical_sha256":"9bc083938072d936b3f6db53e5546f1d090c923d36b328ca5c391cfa20b8f30f","source":{"kind":"arxiv","id":"2002.02562","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.02562","created_at":"2026-07-05T00:41:03Z"},{"alias_kind":"arxiv_version","alias_value":"2002.02562v2","created_at":"2026-07-05T00:41:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.02562","created_at":"2026-07-05T00:41:03Z"},{"alias_kind":"pith_short_12","alias_value":"TPAIHE4AOLMT","created_at":"2026-07-05T00:41:03Z"},{"alias_kind":"pith_short_16","alias_value":"TPAIHE4AOLMTNM7W","created_at":"2026-07-05T00:41:03Z"},{"alias_kind":"pith_short_8","alias_value":"TPAIHE4A","created_at":"2026-07-05T00:41:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:TPAIHE4AOLMTNM7W3NJ6KVDPDU","target":"record","payload":{"canonical_record":{"source":{"id":"2002.02562","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-02-07T00:04:04Z","cross_cats_sorted":["cs.CL","cs.SD"],"title_canon_sha256":"9362875260d778da20f17d673bbae44fced2687df3faef51a74ca681422bba7d","abstract_canon_sha256":"baf50dbebddf980c2018d6e5a831e4f43bce942d2f631fe53c6b54a4eb319442"},"schema_version":"1.0"},"canonical_sha256":"9bc083938072d936b3f6db53e5546f1d090c923d36b328ca5c391cfa20b8f30f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:41:03.358724Z","signature_b64":"KD7NnOLiq9YOt3yQaTfyWRAPc8VqBpobN6+jxOuR8jJ9OZqxIktauClwzBOUNlQqlicAIS/VaT96NS2o8x+2AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9bc083938072d936b3f6db53e5546f1d090c923d36b328ca5c391cfa20b8f30f","last_reissued_at":"2026-07-05T00:41:03.358236Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:41:03.358236Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.02562","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":"2026-07-05T00:41:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EKRoxA1SSZPNdZbE4xw5P0nYOOvMYE6/ohhI9+k497R12/b97A3i1rsvyeJxDdHTwI/Uop3h0vHH8mBk9U2pBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T16:10:36.112882Z"},"content_sha256":"935832352033fa347e6c189b14a788bd25bfbc05db6a02d8e6b27fa6ea187f69","schema_version":"1.0","event_id":"sha256:935832352033fa347e6c189b14a788bd25bfbc05db6a02d8e6b27fa6ea187f69"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:TPAIHE4AOLMTNM7W3NJ6KVDPDU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Transformer Transducer: A Streamable Speech Recognition Model with Transformer Encoders and RNN-T Loss","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.SD"],"primary_cat":"eess.AS","authors_text":"Anshuman Tripathi, Erik McDermott, Han Lu, Hasim Sak, Qian Zhang, Shankar Kumar, Stephen Koo","submitted_at":"2020-02-07T00:04:04Z","abstract_excerpt":"In this paper we present an end-to-end speech recognition model with Transformer encoders that can be used in a streaming speech recognition system. Transformer computation blocks based on self-attention are used to encode both audio and label sequences independently. The activations from both audio and label encoders are combined with a feed-forward layer to compute a probability distribution over the label space for every combination of acoustic frame position and label history. This is similar to the Recurrent Neural Network Transducer (RNN-T) model, which uses RNNs for information encoding"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.02562","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/2002.02562/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":"2026-07-05T00:41:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"75meHVB1cuHYbIaCaiN82WVB6MbNAmIgX2DjS2eeQXRm6PBhEJPKJ28gMQy5SIl1EhBxpuhFs9Atkx0oV8rBDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T16:10:36.113393Z"},"content_sha256":"2e1f0083a2fdb64580c0ba6e6faf3d0c716723d4f8d0ee22effaac3566af23ea","schema_version":"1.0","event_id":"sha256:2e1f0083a2fdb64580c0ba6e6faf3d0c716723d4f8d0ee22effaac3566af23ea"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TPAIHE4AOLMTNM7W3NJ6KVDPDU/bundle.json","state_url":"https://pith.science/pith/TPAIHE4AOLMTNM7W3NJ6KVDPDU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TPAIHE4AOLMTNM7W3NJ6KVDPDU/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":"2026-08-03T16:10:36Z","links":{"resolver":"https://pith.science/pith/TPAIHE4AOLMTNM7W3NJ6KVDPDU","bundle":"https://pith.science/pith/TPAIHE4AOLMTNM7W3NJ6KVDPDU/bundle.json","state":"https://pith.science/pith/TPAIHE4AOLMTNM7W3NJ6KVDPDU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TPAIHE4AOLMTNM7W3NJ6KVDPDU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:TPAIHE4AOLMTNM7W3NJ6KVDPDU","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":"baf50dbebddf980c2018d6e5a831e4f43bce942d2f631fe53c6b54a4eb319442","cross_cats_sorted":["cs.CL","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-02-07T00:04:04Z","title_canon_sha256":"9362875260d778da20f17d673bbae44fced2687df3faef51a74ca681422bba7d"},"schema_version":"1.0","source":{"id":"2002.02562","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.02562","created_at":"2026-07-05T00:41:03Z"},{"alias_kind":"arxiv_version","alias_value":"2002.02562v2","created_at":"2026-07-05T00:41:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.02562","created_at":"2026-07-05T00:41:03Z"},{"alias_kind":"pith_short_12","alias_value":"TPAIHE4AOLMT","created_at":"2026-07-05T00:41:03Z"},{"alias_kind":"pith_short_16","alias_value":"TPAIHE4AOLMTNM7W","created_at":"2026-07-05T00:41:03Z"},{"alias_kind":"pith_short_8","alias_value":"TPAIHE4A","created_at":"2026-07-05T00:41:03Z"}],"graph_snapshots":[{"event_id":"sha256:2e1f0083a2fdb64580c0ba6e6faf3d0c716723d4f8d0ee22effaac3566af23ea","target":"graph","created_at":"2026-07-05T00:41:03Z","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/2002.02562/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper we present an end-to-end speech recognition model with Transformer encoders that can be used in a streaming speech recognition system. Transformer computation blocks based on self-attention are used to encode both audio and label sequences independently. The activations from both audio and label encoders are combined with a feed-forward layer to compute a probability distribution over the label space for every combination of acoustic frame position and label history. This is similar to the Recurrent Neural Network Transducer (RNN-T) model, which uses RNNs for information encoding","authors_text":"Anshuman Tripathi, Erik McDermott, Han Lu, Hasim Sak, Qian Zhang, Shankar Kumar, Stephen Koo","cross_cats":["cs.CL","cs.SD"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-02-07T00:04:04Z","title":"Transformer Transducer: A Streamable Speech Recognition Model with Transformer Encoders and RNN-T Loss"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.02562","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":"sha256:935832352033fa347e6c189b14a788bd25bfbc05db6a02d8e6b27fa6ea187f69","target":"record","created_at":"2026-07-05T00:41:03Z","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":"baf50dbebddf980c2018d6e5a831e4f43bce942d2f631fe53c6b54a4eb319442","cross_cats_sorted":["cs.CL","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-02-07T00:04:04Z","title_canon_sha256":"9362875260d778da20f17d673bbae44fced2687df3faef51a74ca681422bba7d"},"schema_version":"1.0","source":{"id":"2002.02562","kind":"arxiv","version":2}},"canonical_sha256":"9bc083938072d936b3f6db53e5546f1d090c923d36b328ca5c391cfa20b8f30f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9bc083938072d936b3f6db53e5546f1d090c923d36b328ca5c391cfa20b8f30f","first_computed_at":"2026-07-05T00:41:03.358236Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:41:03.358236Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KD7NnOLiq9YOt3yQaTfyWRAPc8VqBpobN6+jxOuR8jJ9OZqxIktauClwzBOUNlQqlicAIS/VaT96NS2o8x+2AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:41:03.358724Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.02562","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:935832352033fa347e6c189b14a788bd25bfbc05db6a02d8e6b27fa6ea187f69","sha256:2e1f0083a2fdb64580c0ba6e6faf3d0c716723d4f8d0ee22effaac3566af23ea"],"state_sha256":"dcd06f1424ee863d13e745d4cc7703dae4cf47200835da85bc54c3b16bddbd6a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EJ3UvyAN+44/L3/JW63F9Z5UbrN9mQ9G1Io8+yFycUijGGRbSJE+aTaEIOcfrHdGZWrbgidZvG9fm8cG6pENCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T16:10:36.118412Z","bundle_sha256":"f129422f5dcacdc83a2b37d714560308e2d969d5518be9a3693b26f8add10f50"}}