{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:DL7L5M43JCSUGAMZ33CH7BZPKC","short_pith_number":"pith:DL7L5M43","schema_version":"1.0","canonical_sha256":"1afebeb39b48a5430199dec47f872f508bd8528caee2fdad0477c048c81e2de1","source":{"kind":"arxiv","id":"2203.00236","version":2},"attestation_state":"computed","paper":{"title":"TRILLsson: Distilled Universal Paralinguistic Speech Representations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.LG","cs.SD"],"primary_cat":"eess.AS","authors_text":"Joel Shor, Subhashini Venugopalan","submitted_at":"2022-03-01T05:22:57Z","abstract_excerpt":"Recent advances in self-supervision have dramatically improved the quality of speech representations. However, deployment of state-of-the-art embedding models on devices has been restricted due to their limited public availability and large resource footprint. Our work addresses these issues by publicly releasing a collection of paralinguistic speech models that are small and near state-of-the-art performance. Our approach is based on knowledge distillation, and our models are distilled on public data only. We explore different architectures and thoroughly evaluate our models on the Non-Semant"},"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":"2203.00236","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-03-01T05:22:57Z","cross_cats_sorted":["cs.CL","cs.LG","cs.SD"],"title_canon_sha256":"b71b28ec3ebb7e7389c94eac4e260047b012e835edd530331bd9303fe197a0bb","abstract_canon_sha256":"3618092dbe235ee4f4d8dba98c5a5af368a0aa9f7f36f81b2881bad0827bc02e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:26:04.221076Z","signature_b64":"owcBEPk9amgYxXGAJc6BRvdz5RDtXphKRcDGnm1OVdEq+Xtc2UMPh6ZqIa3ueQTAs3fXaN3JuTCzun4KT9X9Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1afebeb39b48a5430199dec47f872f508bd8528caee2fdad0477c048c81e2de1","last_reissued_at":"2026-07-05T05:26:04.220678Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:26:04.220678Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"TRILLsson: Distilled Universal Paralinguistic Speech Representations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.LG","cs.SD"],"primary_cat":"eess.AS","authors_text":"Joel Shor, Subhashini Venugopalan","submitted_at":"2022-03-01T05:22:57Z","abstract_excerpt":"Recent advances in self-supervision have dramatically improved the quality of speech representations. However, deployment of state-of-the-art embedding models on devices has been restricted due to their limited public availability and large resource footprint. Our work addresses these issues by publicly releasing a collection of paralinguistic speech models that are small and near state-of-the-art performance. Our approach is based on knowledge distillation, and our models are distilled on public data only. We explore different architectures and thoroughly evaluate our models on the Non-Semant"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.00236","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/2203.00236/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":"2203.00236","created_at":"2026-07-05T05:26:04.220741+00:00"},{"alias_kind":"arxiv_version","alias_value":"2203.00236v2","created_at":"2026-07-05T05:26:04.220741+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.00236","created_at":"2026-07-05T05:26:04.220741+00:00"},{"alias_kind":"pith_short_12","alias_value":"DL7L5M43JCSU","created_at":"2026-07-05T05:26:04.220741+00:00"},{"alias_kind":"pith_short_16","alias_value":"DL7L5M43JCSUGAMZ","created_at":"2026-07-05T05:26:04.220741+00:00"},{"alias_kind":"pith_short_8","alias_value":"DL7L5M43","created_at":"2026-07-05T05:26:04.220741+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2509.00186","citing_title":"Generalizable Audio Spoofing Detection using Non-Semantic Representations","ref_index":33,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DL7L5M43JCSUGAMZ33CH7BZPKC","json":"https://pith.science/pith/DL7L5M43JCSUGAMZ33CH7BZPKC.json","graph_json":"https://pith.science/api/pith-number/DL7L5M43JCSUGAMZ33CH7BZPKC/graph.json","events_json":"https://pith.science/api/pith-number/DL7L5M43JCSUGAMZ33CH7BZPKC/events.json","paper":"https://pith.science/paper/DL7L5M43"},"agent_actions":{"view_html":"https://pith.science/pith/DL7L5M43JCSUGAMZ33CH7BZPKC","download_json":"https://pith.science/pith/DL7L5M43JCSUGAMZ33CH7BZPKC.json","view_paper":"https://pith.science/paper/DL7L5M43","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2203.00236&json=true","fetch_graph":"https://pith.science/api/pith-number/DL7L5M43JCSUGAMZ33CH7BZPKC/graph.json","fetch_events":"https://pith.science/api/pith-number/DL7L5M43JCSUGAMZ33CH7BZPKC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DL7L5M43JCSUGAMZ33CH7BZPKC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DL7L5M43JCSUGAMZ33CH7BZPKC/action/storage_attestation","attest_author":"https://pith.science/pith/DL7L5M43JCSUGAMZ33CH7BZPKC/action/author_attestation","sign_citation":"https://pith.science/pith/DL7L5M43JCSUGAMZ33CH7BZPKC/action/citation_signature","submit_replication":"https://pith.science/pith/DL7L5M43JCSUGAMZ33CH7BZPKC/action/replication_record"}},"created_at":"2026-07-05T05:26:04.220741+00:00","updated_at":"2026-07-05T05:26:04.220741+00:00"}