{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:LEKC47CQ2N6NDI4GSAKTGPETLU","short_pith_number":"pith:LEKC47CQ","schema_version":"1.0","canonical_sha256":"59142e7c50d37cd1a3869015333c935d03eb460673af9a676776d1a9b431e25f","source":{"kind":"arxiv","id":"2505.00059","version":2},"attestation_state":"computed","paper":{"title":"BERSting at the Screams: A Benchmark for Distanced, Emotional and Shouted Speech Recognition","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.SD","eess.AS"],"primary_cat":"cs.CL","authors_text":"Angelica Lim, Avni Kapoor, Luna Sang, Mantaj Dhillon, Paige Tutt\\\"os\\'i, Poorvi Bhatia, Quang Minh Dinh, Shane Eastwood, Yewon Jin","submitted_at":"2025-04-30T14:08:14Z","abstract_excerpt":"Some speech recognition tasks, such as automatic speech recognition (ASR), are approaching or have reached human performance in many reported metrics. Yet, they continue to struggle in complex, real-world, situations, such as with distanced speech. Previous challenges have released datasets to address the issue of distanced ASR, however, the focus remains primarily on distance, specifically relying on multi-microphone array systems. Here we present the B(asic) E(motion) R(andom phrase) S(hou)t(s) (BERSt) dataset. The dataset contains almost 4 hours of English speech from 98 actors with varying"},"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":"2505.00059","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-30T14:08:14Z","cross_cats_sorted":["cs.SD","eess.AS"],"title_canon_sha256":"ed70cd472d552e4898b96ae615096c1979d98153bddfdf376188fbbd8cbda6de","abstract_canon_sha256":"b0133d57afd3cf292b42b2ff33ee2878d695cd8acdb366c7ec5f5e1bba6970dd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:45:34.491071Z","signature_b64":"hn/w7hkk02RS2XdYNQ80xhR0vSs6789nRefHZmeGnBUpHuQP29zl655bP35Qi6ijf8ngGxAxHxNOZ5agoFqVBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59142e7c50d37cd1a3869015333c935d03eb460673af9a676776d1a9b431e25f","last_reissued_at":"2026-07-05T11:45:34.490589Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:45:34.490589Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"BERSting at the Screams: A Benchmark for Distanced, Emotional and Shouted Speech Recognition","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.SD","eess.AS"],"primary_cat":"cs.CL","authors_text":"Angelica Lim, Avni Kapoor, Luna Sang, Mantaj Dhillon, Paige Tutt\\\"os\\'i, Poorvi Bhatia, Quang Minh Dinh, Shane Eastwood, Yewon Jin","submitted_at":"2025-04-30T14:08:14Z","abstract_excerpt":"Some speech recognition tasks, such as automatic speech recognition (ASR), are approaching or have reached human performance in many reported metrics. Yet, they continue to struggle in complex, real-world, situations, such as with distanced speech. Previous challenges have released datasets to address the issue of distanced ASR, however, the focus remains primarily on distance, specifically relying on multi-microphone array systems. Here we present the B(asic) E(motion) R(andom phrase) S(hou)t(s) (BERSt) dataset. The dataset contains almost 4 hours of English speech from 98 actors with varying"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.00059","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/2505.00059/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":"2505.00059","created_at":"2026-07-05T11:45:34.490640+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.00059v2","created_at":"2026-07-05T11:45:34.490640+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.00059","created_at":"2026-07-05T11:45:34.490640+00:00"},{"alias_kind":"pith_short_12","alias_value":"LEKC47CQ2N6N","created_at":"2026-07-05T11:45:34.490640+00:00"},{"alias_kind":"pith_short_16","alias_value":"LEKC47CQ2N6NDI4G","created_at":"2026-07-05T11:45:34.490640+00:00"},{"alias_kind":"pith_short_8","alias_value":"LEKC47CQ","created_at":"2026-07-05T11:45:34.490640+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/LEKC47CQ2N6NDI4GSAKTGPETLU","json":"https://pith.science/pith/LEKC47CQ2N6NDI4GSAKTGPETLU.json","graph_json":"https://pith.science/api/pith-number/LEKC47CQ2N6NDI4GSAKTGPETLU/graph.json","events_json":"https://pith.science/api/pith-number/LEKC47CQ2N6NDI4GSAKTGPETLU/events.json","paper":"https://pith.science/paper/LEKC47CQ"},"agent_actions":{"view_html":"https://pith.science/pith/LEKC47CQ2N6NDI4GSAKTGPETLU","download_json":"https://pith.science/pith/LEKC47CQ2N6NDI4GSAKTGPETLU.json","view_paper":"https://pith.science/paper/LEKC47CQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.00059&json=true","fetch_graph":"https://pith.science/api/pith-number/LEKC47CQ2N6NDI4GSAKTGPETLU/graph.json","fetch_events":"https://pith.science/api/pith-number/LEKC47CQ2N6NDI4GSAKTGPETLU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LEKC47CQ2N6NDI4GSAKTGPETLU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LEKC47CQ2N6NDI4GSAKTGPETLU/action/storage_attestation","attest_author":"https://pith.science/pith/LEKC47CQ2N6NDI4GSAKTGPETLU/action/author_attestation","sign_citation":"https://pith.science/pith/LEKC47CQ2N6NDI4GSAKTGPETLU/action/citation_signature","submit_replication":"https://pith.science/pith/LEKC47CQ2N6NDI4GSAKTGPETLU/action/replication_record"}},"created_at":"2026-07-05T11:45:34.490640+00:00","updated_at":"2026-07-05T11:45:34.490640+00:00"}