{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:K3K3AKQJLTNBRXGGCNHT32OTHG","short_pith_number":"pith:K3K3AKQJ","schema_version":"1.0","canonical_sha256":"56d5b02a095cda18dcc6134f3de9d339a72e02c1de535f71f2d36010f7082999","source":{"kind":"arxiv","id":"2006.05257","version":1},"attestation_state":"computed","paper":{"title":"Learning not to Discriminate: Task Agnostic Learning for Improving Monolingual and Code-switched Speech Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.SD"],"primary_cat":"eess.AS","authors_text":"Basil Abraham, Gurunath Reddy Madhumani, Sanket Shah, Sunayana Sitaram, Vikas Joshi","submitted_at":"2020-06-09T13:45:30Z","abstract_excerpt":"Recognizing code-switched speech is challenging for Automatic Speech Recognition (ASR) for a variety of reasons, including the lack of code-switched training data. Recently, we showed that monolingual ASR systems fine-tuned on code-switched data deteriorate in performance on monolingual speech recognition, which is not desirable as ASR systems deployed in multilingual scenarios should recognize both monolingual and code-switched speech with high accuracy. Our experiments indicated that this loss in performance could be mitigated by using certain strategies for fine-tuning and regularization, l"},"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":"2006.05257","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-06-09T13:45:30Z","cross_cats_sorted":["cs.CL","cs.SD"],"title_canon_sha256":"8a76c751dc81c366334fb4ba6376a6bdd9bddd97a03c95c901321a8dca78c833","abstract_canon_sha256":"0ee6e7d644108795c5552ddcf869c715e3735fd1cd984e9b9174852c9ef54485"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:09:12.176185Z","signature_b64":"G1JOEmj8Lo91lMTIPM14SV9o/qoR3WmJ7YQijBLxVa29r8vUgaiLxzK/2pjIE5vhJSRY5VDxsXTssgy8w65vAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"56d5b02a095cda18dcc6134f3de9d339a72e02c1de535f71f2d36010f7082999","last_reissued_at":"2026-07-05T01:09:12.175820Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:09:12.175820Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning not to Discriminate: Task Agnostic Learning for Improving Monolingual and Code-switched Speech Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.SD"],"primary_cat":"eess.AS","authors_text":"Basil Abraham, Gurunath Reddy Madhumani, Sanket Shah, Sunayana Sitaram, Vikas Joshi","submitted_at":"2020-06-09T13:45:30Z","abstract_excerpt":"Recognizing code-switched speech is challenging for Automatic Speech Recognition (ASR) for a variety of reasons, including the lack of code-switched training data. Recently, we showed that monolingual ASR systems fine-tuned on code-switched data deteriorate in performance on monolingual speech recognition, which is not desirable as ASR systems deployed in multilingual scenarios should recognize both monolingual and code-switched speech with high accuracy. Our experiments indicated that this loss in performance could be mitigated by using certain strategies for fine-tuning and regularization, l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.05257","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/2006.05257/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":"2006.05257","created_at":"2026-07-05T01:09:12.175878+00:00"},{"alias_kind":"arxiv_version","alias_value":"2006.05257v1","created_at":"2026-07-05T01:09:12.175878+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.05257","created_at":"2026-07-05T01:09:12.175878+00:00"},{"alias_kind":"pith_short_12","alias_value":"K3K3AKQJLTNB","created_at":"2026-07-05T01:09:12.175878+00:00"},{"alias_kind":"pith_short_16","alias_value":"K3K3AKQJLTNBRXGG","created_at":"2026-07-05T01:09:12.175878+00:00"},{"alias_kind":"pith_short_8","alias_value":"K3K3AKQJ","created_at":"2026-07-05T01:09:12.175878+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/K3K3AKQJLTNBRXGGCNHT32OTHG","json":"https://pith.science/pith/K3K3AKQJLTNBRXGGCNHT32OTHG.json","graph_json":"https://pith.science/api/pith-number/K3K3AKQJLTNBRXGGCNHT32OTHG/graph.json","events_json":"https://pith.science/api/pith-number/K3K3AKQJLTNBRXGGCNHT32OTHG/events.json","paper":"https://pith.science/paper/K3K3AKQJ"},"agent_actions":{"view_html":"https://pith.science/pith/K3K3AKQJLTNBRXGGCNHT32OTHG","download_json":"https://pith.science/pith/K3K3AKQJLTNBRXGGCNHT32OTHG.json","view_paper":"https://pith.science/paper/K3K3AKQJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2006.05257&json=true","fetch_graph":"https://pith.science/api/pith-number/K3K3AKQJLTNBRXGGCNHT32OTHG/graph.json","fetch_events":"https://pith.science/api/pith-number/K3K3AKQJLTNBRXGGCNHT32OTHG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/K3K3AKQJLTNBRXGGCNHT32OTHG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/K3K3AKQJLTNBRXGGCNHT32OTHG/action/storage_attestation","attest_author":"https://pith.science/pith/K3K3AKQJLTNBRXGGCNHT32OTHG/action/author_attestation","sign_citation":"https://pith.science/pith/K3K3AKQJLTNBRXGGCNHT32OTHG/action/citation_signature","submit_replication":"https://pith.science/pith/K3K3AKQJLTNBRXGGCNHT32OTHG/action/replication_record"}},"created_at":"2026-07-05T01:09:12.175878+00:00","updated_at":"2026-07-05T01:09:12.175878+00:00"}