{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:BWJERMYEN4EUG3LX2UTOR5URTS","short_pith_number":"pith:BWJERMYE","canonical_record":{"source":{"id":"1906.09426","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-06-22T10:23:42Z","cross_cats_sorted":["cs.CL","cs.LG","cs.SD"],"title_canon_sha256":"cc328a7ebd233f252da3407aa12e3e9b69e0641a74e109146d21167f3157235f","abstract_canon_sha256":"882faf7f5874820a676b33ec7081280ddb3eb3724b17176c5070573eafb4088c"},"schema_version":"1.0"},"canonical_sha256":"0d9248b3046f09436d77d526e8f6919ca22dd0ec960afe819f715cc8b7cc15ff","source":{"kind":"arxiv","id":"1906.09426","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.09426","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"arxiv_version","alias_value":"1906.09426v1","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.09426","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"pith_short_12","alias_value":"BWJERMYEN4EU","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"BWJERMYEN4EUG3LX","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"BWJERMYE","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:BWJERMYEN4EUG3LX2UTOR5URTS","target":"record","payload":{"canonical_record":{"source":{"id":"1906.09426","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-06-22T10:23:42Z","cross_cats_sorted":["cs.CL","cs.LG","cs.SD"],"title_canon_sha256":"cc328a7ebd233f252da3407aa12e3e9b69e0641a74e109146d21167f3157235f","abstract_canon_sha256":"882faf7f5874820a676b33ec7081280ddb3eb3724b17176c5070573eafb4088c"},"schema_version":"1.0"},"canonical_sha256":"0d9248b3046f09436d77d526e8f6919ca22dd0ec960afe819f715cc8b7cc15ff","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:38.120143Z","signature_b64":"yW6wpiiAb/d90oIVJdALiPJJUhoVqEXlnVNEs1sEJWhESpZDqytprKS5HNtSrC7yMXu/luX8kq33ClXqABxXAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0d9248b3046f09436d77d526e8f6919ca22dd0ec960afe819f715cc8b7cc15ff","last_reissued_at":"2026-05-17T23:42:38.119415Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:38.119415Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.09426","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":"2026-05-17T23:42:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ST36EiLkztNOrdWGx/v3wN1xPZ2zxvrwuK3NvExk8sovnhvvjmaJDsrDbXxmdPJurbZhoM7RlRriNAegfcK/Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T01:37:35.668976Z"},"content_sha256":"9e24266863cf50bf939c0669bcd1f0674e37af097374d15ed1e7271b40998cb0","schema_version":"1.0","event_id":"sha256:9e24266863cf50bf939c0669bcd1f0674e37af097374d15ed1e7271b40998cb0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:BWJERMYEN4EUG3LX2UTOR5URTS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"End-to-End ASR for Code-switched Hindi-English Speech","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.LG","cs.SD"],"primary_cat":"eess.AS","authors_text":"Basil Abraham, Brij Mohan Lal Srivastava, Preethi Jyothi, Rupesh Mehta, Sunayana Sitaram","submitted_at":"2019-06-22T10:23:42Z","abstract_excerpt":"End-to-end (E2E) models have been explored for large speech corpora and have been found to match or outperform traditional pipeline-based systems in some languages. However, most prior work on end-to-end models use speech corpora exceeding hundreds or thousands of hours. In this study, we explore end-to-end models for code-switched Hindi-English language with less than 50 hours of data. We utilize two specific measures to improve network performance in the low-resource setting, namely multi-task learning (MTL) and balancing the corpus to deal with the inherent class imbalance problem i.e. the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.09426","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":""},"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":"2026-05-17T23:42:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jbtLBrAX0pjGN10H3QDkcNzJNpcnEgTYZYKk0Zvb6KXcyHaLD4/R6wByNilaYwKHGuaR/PPtMLgqSG+GtVh4Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T01:37:35.669629Z"},"content_sha256":"f73b528ace5da11513e2b48615e6af0021ba7cde8aad57b5334246bf155f420a","schema_version":"1.0","event_id":"sha256:f73b528ace5da11513e2b48615e6af0021ba7cde8aad57b5334246bf155f420a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BWJERMYEN4EUG3LX2UTOR5URTS/bundle.json","state_url":"https://pith.science/pith/BWJERMYEN4EUG3LX2UTOR5URTS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BWJERMYEN4EUG3LX2UTOR5URTS/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":"2026-05-26T01:37:35Z","links":{"resolver":"https://pith.science/pith/BWJERMYEN4EUG3LX2UTOR5URTS","bundle":"https://pith.science/pith/BWJERMYEN4EUG3LX2UTOR5URTS/bundle.json","state":"https://pith.science/pith/BWJERMYEN4EUG3LX2UTOR5URTS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BWJERMYEN4EUG3LX2UTOR5URTS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:BWJERMYEN4EUG3LX2UTOR5URTS","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":"882faf7f5874820a676b33ec7081280ddb3eb3724b17176c5070573eafb4088c","cross_cats_sorted":["cs.CL","cs.LG","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-06-22T10:23:42Z","title_canon_sha256":"cc328a7ebd233f252da3407aa12e3e9b69e0641a74e109146d21167f3157235f"},"schema_version":"1.0","source":{"id":"1906.09426","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.09426","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"arxiv_version","alias_value":"1906.09426v1","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.09426","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"pith_short_12","alias_value":"BWJERMYEN4EU","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"BWJERMYEN4EUG3LX","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"BWJERMYE","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:f73b528ace5da11513e2b48615e6af0021ba7cde8aad57b5334246bf155f420a","target":"graph","created_at":"2026-05-17T23:42:38Z","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"},"paper":{"abstract_excerpt":"End-to-end (E2E) models have been explored for large speech corpora and have been found to match or outperform traditional pipeline-based systems in some languages. However, most prior work on end-to-end models use speech corpora exceeding hundreds or thousands of hours. In this study, we explore end-to-end models for code-switched Hindi-English language with less than 50 hours of data. We utilize two specific measures to improve network performance in the low-resource setting, namely multi-task learning (MTL) and balancing the corpus to deal with the inherent class imbalance problem i.e. the ","authors_text":"Basil Abraham, Brij Mohan Lal Srivastava, Preethi Jyothi, Rupesh Mehta, Sunayana Sitaram","cross_cats":["cs.CL","cs.LG","cs.SD"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-06-22T10:23:42Z","title":"End-to-End ASR for Code-switched Hindi-English Speech"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.09426","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":"sha256:9e24266863cf50bf939c0669bcd1f0674e37af097374d15ed1e7271b40998cb0","target":"record","created_at":"2026-05-17T23:42:38Z","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":"882faf7f5874820a676b33ec7081280ddb3eb3724b17176c5070573eafb4088c","cross_cats_sorted":["cs.CL","cs.LG","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2019-06-22T10:23:42Z","title_canon_sha256":"cc328a7ebd233f252da3407aa12e3e9b69e0641a74e109146d21167f3157235f"},"schema_version":"1.0","source":{"id":"1906.09426","kind":"arxiv","version":1}},"canonical_sha256":"0d9248b3046f09436d77d526e8f6919ca22dd0ec960afe819f715cc8b7cc15ff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0d9248b3046f09436d77d526e8f6919ca22dd0ec960afe819f715cc8b7cc15ff","first_computed_at":"2026-05-17T23:42:38.119415Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:38.119415Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yW6wpiiAb/d90oIVJdALiPJJUhoVqEXlnVNEs1sEJWhESpZDqytprKS5HNtSrC7yMXu/luX8kq33ClXqABxXAQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:38.120143Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.09426","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9e24266863cf50bf939c0669bcd1f0674e37af097374d15ed1e7271b40998cb0","sha256:f73b528ace5da11513e2b48615e6af0021ba7cde8aad57b5334246bf155f420a"],"state_sha256":"fc65817b50c2e9f65eb74f5b0c664fcc04ada01ff46914c88568a029bff54390"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O8koXlskYjTxrMvzgGRlJXX/bBkXC5ViF7gID6V5WOQdDdzBqULJVrCDi97hBebsAKIoyh/k+FqguB7zpSTNCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T01:37:35.672863Z","bundle_sha256":"498890633a46051f169ad3aaf637a6d26f47ae4d0e1cbf17e9bd182bd979349c"}}