{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:ELO6OBXGZ63M4HFLV6HLSHVGUZ","short_pith_number":"pith:ELO6OBXG","schema_version":"1.0","canonical_sha256":"22dde706e6cfb6ce1cabaf8eb91ea6a66933b82bedb49c5fa42c1f92be68e257","source":{"kind":"arxiv","id":"2005.14489","version":1},"attestation_state":"computed","paper":{"title":"Neural Simultaneous Speech Translation Using Alignment-Based Chunking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Evgeny Matusov, Patrick Wilken, Pavel Golik, Tamer Alkhouli","submitted_at":"2020-05-29T10:20:48Z","abstract_excerpt":"In simultaneous machine translation, the objective is to determine when to produce a partial translation given a continuous stream of source words, with a trade-off between latency and quality. We propose a neural machine translation (NMT) model that makes dynamic decisions when to continue feeding on input or generate output words. The model is composed of two main components: one to dynamically decide on ending a source chunk, and another that translates the consumed chunk. We train the components jointly and in a manner consistent with the inference conditions. To generate chunked training "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2005.14489","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-29T10:20:48Z","cross_cats_sorted":[],"title_canon_sha256":"bbf2903785c6c1d638f395ab51a2cb44779ab4dd73a9df24bd809f2e058dd480","abstract_canon_sha256":"6288a88418521d36c09689c430895f0c32bdefd0b71b980f0c69f65870ed87a7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:06:37.350945Z","signature_b64":"4LCYgzZCt6bM2p8dO2rk+iENdvx2ImkaWZRksK9pbbWqPMHnWx+WhD+Zpeie7hwRQEl6pMRbNEkc0xND08KDAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22dde706e6cfb6ce1cabaf8eb91ea6a66933b82bedb49c5fa42c1f92be68e257","last_reissued_at":"2026-07-05T01:06:37.350481Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:06:37.350481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Neural Simultaneous Speech Translation Using Alignment-Based Chunking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Evgeny Matusov, Patrick Wilken, Pavel Golik, Tamer Alkhouli","submitted_at":"2020-05-29T10:20:48Z","abstract_excerpt":"In simultaneous machine translation, the objective is to determine when to produce a partial translation given a continuous stream of source words, with a trade-off between latency and quality. We propose a neural machine translation (NMT) model that makes dynamic decisions when to continue feeding on input or generate output words. The model is composed of two main components: one to dynamically decide on ending a source chunk, and another that translates the consumed chunk. We train the components jointly and in a manner consistent with the inference conditions. To generate chunked training "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.14489","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/2005.14489/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2005.14489","created_at":"2026-07-05T01:06:37.350536+00:00"},{"alias_kind":"arxiv_version","alias_value":"2005.14489v1","created_at":"2026-07-05T01:06:37.350536+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.14489","created_at":"2026-07-05T01:06:37.350536+00:00"},{"alias_kind":"pith_short_12","alias_value":"ELO6OBXGZ63M","created_at":"2026-07-05T01:06:37.350536+00:00"},{"alias_kind":"pith_short_16","alias_value":"ELO6OBXGZ63M4HFL","created_at":"2026-07-05T01:06:37.350536+00:00"},{"alias_kind":"pith_short_8","alias_value":"ELO6OBXG","created_at":"2026-07-05T01:06:37.350536+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ","json":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ.json","graph_json":"https://pith.science/api/pith-number/ELO6OBXGZ63M4HFLV6HLSHVGUZ/graph.json","events_json":"https://pith.science/api/pith-number/ELO6OBXGZ63M4HFLV6HLSHVGUZ/events.json","paper":"https://pith.science/paper/ELO6OBXG"},"agent_actions":{"view_html":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ","download_json":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ.json","view_paper":"https://pith.science/paper/ELO6OBXG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2005.14489&json=true","fetch_graph":"https://pith.science/api/pith-number/ELO6OBXGZ63M4HFLV6HLSHVGUZ/graph.json","fetch_events":"https://pith.science/api/pith-number/ELO6OBXGZ63M4HFLV6HLSHVGUZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/action/storage_attestation","attest_author":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/action/author_attestation","sign_citation":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/action/citation_signature","submit_replication":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/action/replication_record"}},"created_at":"2026-07-05T01:06:37.350536+00:00","updated_at":"2026-07-05T01:06:37.350536+00:00"}