{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:VLYMTZKP4Y6ABJ7VQQN6JLJ7HS","short_pith_number":"pith:VLYMTZKP","canonical_record":{"source":{"id":"2310.13013","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-17T14:49:48Z","cross_cats_sorted":["cs.AI","cs.SD","eess.AS"],"title_canon_sha256":"01d1845c6b8bc962b41a7e57a9a275fae6d75075399d1ea2b9461492e75ba25a","abstract_canon_sha256":"c7601d9d4dff95459693170542c6a711854436a93e12f255b611856b042afc8b"},"schema_version":"1.0"},"canonical_sha256":"aaf0c9e54fe63c00a7f5841be4ad3f3cb06e288239d5698ad1948caaeb74192b","source":{"kind":"arxiv","id":"2310.13013","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.13013","created_at":"2026-07-05T07:02:55Z"},{"alias_kind":"arxiv_version","alias_value":"2310.13013v1","created_at":"2026-07-05T07:02:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.13013","created_at":"2026-07-05T07:02:55Z"},{"alias_kind":"pith_short_12","alias_value":"VLYMTZKP4Y6A","created_at":"2026-07-05T07:02:55Z"},{"alias_kind":"pith_short_16","alias_value":"VLYMTZKP4Y6ABJ7V","created_at":"2026-07-05T07:02:55Z"},{"alias_kind":"pith_short_8","alias_value":"VLYMTZKP","created_at":"2026-07-05T07:02:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:VLYMTZKP4Y6ABJ7VQQN6JLJ7HS","target":"record","payload":{"canonical_record":{"source":{"id":"2310.13013","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-17T14:49:48Z","cross_cats_sorted":["cs.AI","cs.SD","eess.AS"],"title_canon_sha256":"01d1845c6b8bc962b41a7e57a9a275fae6d75075399d1ea2b9461492e75ba25a","abstract_canon_sha256":"c7601d9d4dff95459693170542c6a711854436a93e12f255b611856b042afc8b"},"schema_version":"1.0"},"canonical_sha256":"aaf0c9e54fe63c00a7f5841be4ad3f3cb06e288239d5698ad1948caaeb74192b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:02:55.682096Z","signature_b64":"lsdqHH9O0fITEG7NeH5kKw7cRUaCcnkUa+vqDRpPEJDU3bLcTCe0uBq/uy1i1rGJAcD03sHPbOIdziXVZOTyAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aaf0c9e54fe63c00a7f5841be4ad3f3cb06e288239d5698ad1948caaeb74192b","last_reissued_at":"2026-07-05T07:02:55.681643Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:02:55.681643Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.13013","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":"2026-07-05T07:02:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OBqwHrcTs5RW+8D142vmy9ZhCeUS54LLSM7//Ng6IQn+sORtvFLf11SJM0I4ViZVPj0MoFJAulZL2nUZsX31BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T01:13:12.625943Z"},"content_sha256":"78def2a3861853f573d35f9b08047f9113bc102ab9abbcc0175018f3a02d10e0","schema_version":"1.0","event_id":"sha256:78def2a3861853f573d35f9b08047f9113bc102ab9abbcc0175018f3a02d10e0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:VLYMTZKP4Y6ABJ7VQQN6JLJ7HS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generative error correction for code-switching speech recognition using large language models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.SD","eess.AS"],"primary_cat":"cs.CL","authors_text":"Chao-Han Huck Yang, Chen Chen, Eng Siong Chng, Hexin Liu, Sabato Marco Siniscalchi, Yuchen Hu","submitted_at":"2023-10-17T14:49:48Z","abstract_excerpt":"Code-switching (CS) speech refers to the phenomenon of mixing two or more languages within the same sentence. Despite the recent advances in automatic speech recognition (ASR), CS-ASR is still a challenging task ought to the grammatical structure complexity of the phenomenon and the data scarcity of specific training corpus. In this work, we propose to leverage large language models (LLMs) and lists of hypotheses generated by an ASR to address the CS problem. Specifically, we first employ multiple well-trained ASR models for N-best hypotheses generation, with the aim of increasing the diverse "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.13013","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/2310.13013/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":"2026-07-05T07:02:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AKX/+wYcA1vtUUNq5i8mcYhtj6k4KZlCuxNxDvbBdxpMxl7NAKFZlbCUO4HGqSnGU1zd6zLk1maSFt55sz5GDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T01:13:12.626282Z"},"content_sha256":"6bccd9941ece0c08de51d40cf994435526c89bfb078c720ebaf0449ec2d4b115","schema_version":"1.0","event_id":"sha256:6bccd9941ece0c08de51d40cf994435526c89bfb078c720ebaf0449ec2d4b115"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VLYMTZKP4Y6ABJ7VQQN6JLJ7HS/bundle.json","state_url":"https://pith.science/pith/VLYMTZKP4Y6ABJ7VQQN6JLJ7HS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VLYMTZKP4Y6ABJ7VQQN6JLJ7HS/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":"2026-08-19T01:13:12Z","links":{"resolver":"https://pith.science/pith/VLYMTZKP4Y6ABJ7VQQN6JLJ7HS","bundle":"https://pith.science/pith/VLYMTZKP4Y6ABJ7VQQN6JLJ7HS/bundle.json","state":"https://pith.science/pith/VLYMTZKP4Y6ABJ7VQQN6JLJ7HS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VLYMTZKP4Y6ABJ7VQQN6JLJ7HS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:VLYMTZKP4Y6ABJ7VQQN6JLJ7HS","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":"c7601d9d4dff95459693170542c6a711854436a93e12f255b611856b042afc8b","cross_cats_sorted":["cs.AI","cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-17T14:49:48Z","title_canon_sha256":"01d1845c6b8bc962b41a7e57a9a275fae6d75075399d1ea2b9461492e75ba25a"},"schema_version":"1.0","source":{"id":"2310.13013","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.13013","created_at":"2026-07-05T07:02:55Z"},{"alias_kind":"arxiv_version","alias_value":"2310.13013v1","created_at":"2026-07-05T07:02:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.13013","created_at":"2026-07-05T07:02:55Z"},{"alias_kind":"pith_short_12","alias_value":"VLYMTZKP4Y6A","created_at":"2026-07-05T07:02:55Z"},{"alias_kind":"pith_short_16","alias_value":"VLYMTZKP4Y6ABJ7V","created_at":"2026-07-05T07:02:55Z"},{"alias_kind":"pith_short_8","alias_value":"VLYMTZKP","created_at":"2026-07-05T07:02:55Z"}],"graph_snapshots":[{"event_id":"sha256:6bccd9941ece0c08de51d40cf994435526c89bfb078c720ebaf0449ec2d4b115","target":"graph","created_at":"2026-07-05T07:02:55Z","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/2310.13013/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Code-switching (CS) speech refers to the phenomenon of mixing two or more languages within the same sentence. Despite the recent advances in automatic speech recognition (ASR), CS-ASR is still a challenging task ought to the grammatical structure complexity of the phenomenon and the data scarcity of specific training corpus. In this work, we propose to leverage large language models (LLMs) and lists of hypotheses generated by an ASR to address the CS problem. Specifically, we first employ multiple well-trained ASR models for N-best hypotheses generation, with the aim of increasing the diverse ","authors_text":"Chao-Han Huck Yang, Chen Chen, Eng Siong Chng, Hexin Liu, Sabato Marco Siniscalchi, Yuchen Hu","cross_cats":["cs.AI","cs.SD","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-17T14:49:48Z","title":"Generative error correction for code-switching speech recognition using large language models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.13013","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":"sha256:78def2a3861853f573d35f9b08047f9113bc102ab9abbcc0175018f3a02d10e0","target":"record","created_at":"2026-07-05T07:02:55Z","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":"c7601d9d4dff95459693170542c6a711854436a93e12f255b611856b042afc8b","cross_cats_sorted":["cs.AI","cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-17T14:49:48Z","title_canon_sha256":"01d1845c6b8bc962b41a7e57a9a275fae6d75075399d1ea2b9461492e75ba25a"},"schema_version":"1.0","source":{"id":"2310.13013","kind":"arxiv","version":1}},"canonical_sha256":"aaf0c9e54fe63c00a7f5841be4ad3f3cb06e288239d5698ad1948caaeb74192b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aaf0c9e54fe63c00a7f5841be4ad3f3cb06e288239d5698ad1948caaeb74192b","first_computed_at":"2026-07-05T07:02:55.681643Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:02:55.681643Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lsdqHH9O0fITEG7NeH5kKw7cRUaCcnkUa+vqDRpPEJDU3bLcTCe0uBq/uy1i1rGJAcD03sHPbOIdziXVZOTyAw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:02:55.682096Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.13013","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:78def2a3861853f573d35f9b08047f9113bc102ab9abbcc0175018f3a02d10e0","sha256:6bccd9941ece0c08de51d40cf994435526c89bfb078c720ebaf0449ec2d4b115"],"state_sha256":"40df44fa9711ab08b4b39c422116c9e6708f7b9934debe24564486da29f4ee98"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bSS/+YVxoydM0BZzmGeH98MxMcdQIgeJUxyBJZGIwTwZ/6B7mHQG8L8a2og/nHxQgWpr2qgB+XRb5UfSyNXWDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T01:13:12.629520Z","bundle_sha256":"1b83195e7b122db718e6d8a0886aeed1730d9b3d28888a69a840a31858a34d69"}}