{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:IICVHHVNWCNGPGD54AFAKN7XCD","short_pith_number":"pith:IICVHHVN","canonical_record":{"source":{"id":"2406.15723","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-22T03:56:29Z","cross_cats_sorted":["cs.AI","cs.SD","eess.AS"],"title_canon_sha256":"669c690ac5637dc03a4907e5e22e5b837bbc6c99454bfedfb958e353bca28c97","abstract_canon_sha256":"2cf123ec06b2ab460ac282edd613aa83d56ede63008eba99dab9d707ebfeba9b"},"schema_version":"1.0"},"canonical_sha256":"4205539eadb09a67987de00a0537f710d72ae341639d893c839f680d5fa189ec","source":{"kind":"arxiv","id":"2406.15723","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.15723","created_at":"2026-07-05T08:35:49Z"},{"alias_kind":"arxiv_version","alias_value":"2406.15723v1","created_at":"2026-07-05T08:35:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.15723","created_at":"2026-07-05T08:35:49Z"},{"alias_kind":"pith_short_12","alias_value":"IICVHHVNWCNG","created_at":"2026-07-05T08:35:49Z"},{"alias_kind":"pith_short_16","alias_value":"IICVHHVNWCNGPGD5","created_at":"2026-07-05T08:35:49Z"},{"alias_kind":"pith_short_8","alias_value":"IICVHHVN","created_at":"2026-07-05T08:35:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:IICVHHVNWCNGPGD54AFAKN7XCD","target":"record","payload":{"canonical_record":{"source":{"id":"2406.15723","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-22T03:56:29Z","cross_cats_sorted":["cs.AI","cs.SD","eess.AS"],"title_canon_sha256":"669c690ac5637dc03a4907e5e22e5b837bbc6c99454bfedfb958e353bca28c97","abstract_canon_sha256":"2cf123ec06b2ab460ac282edd613aa83d56ede63008eba99dab9d707ebfeba9b"},"schema_version":"1.0"},"canonical_sha256":"4205539eadb09a67987de00a0537f710d72ae341639d893c839f680d5fa189ec","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:35:49.041769Z","signature_b64":"JNZGkvOk9Z/EVD9/0tFPFNFthf6IImR2iyVKhiY/YiPvTJInQxAgwjldiMprrXY3AXNkxXHWsck/to5IXMdtDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4205539eadb09a67987de00a0537f710d72ae341639d893c839f680d5fa189ec","last_reissued_at":"2026-07-05T08:35:49.041378Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:35:49.041378Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.15723","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":"2026-07-05T08:35:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YTTLkd0BzPLU+uu2J4keZ1QkNIaXLraouvSW9fu4ST/AhcQq8mtsTGE3egi/dczxFvt4ZLY47TR0j3Ke55/MAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T14:32:39.223275Z"},"content_sha256":"767d787f5502a3552a7c2a4ccca91742786f3111ff0546582a150ec981ca4d85","schema_version":"1.0","event_id":"sha256:767d787f5502a3552a7c2a4ccca91742786f3111ff0546582a150ec981ca4d85"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:IICVHHVNWCNGPGD54AFAKN7XCD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Acoustic Feature Mixup for Balanced Multi-aspect Pronunciation Assessment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.SD","eess.AS"],"primary_cat":"cs.CL","authors_text":"Gary Geunbae Lee, Heejin Do, Wonjun Lee","submitted_at":"2024-06-22T03:56:29Z","abstract_excerpt":"In automated pronunciation assessment, recent emphasis progressively lies on evaluating multiple aspects to provide enriched feedback. However, acquiring multi-aspect-score labeled data for non-native language learners' speech poses challenges; moreover, it often leads to score-imbalanced distributions. In this paper, we propose two Acoustic Feature Mixup strategies, linearly and non-linearly interpolating with the in-batch averaged feature, to address data scarcity and score-label imbalances. Primarily using goodness-of-pronunciation as an acoustic feature, we tailor mixup designs to suit pro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.15723","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/2406.15723/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":"2026-07-05T08:35:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zazXECRqHjqAiuHbHi/WJoKs33jHCsFnohFYxzVva5oYBaf8HKCODSNYRlpEU800GCIdYluSwRrhICM4R9avDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T14:32:39.223841Z"},"content_sha256":"50ac7274211faf29d7051c7c7b49409b756b4d7d87dc451953669a0a98bd0803","schema_version":"1.0","event_id":"sha256:50ac7274211faf29d7051c7c7b49409b756b4d7d87dc451953669a0a98bd0803"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IICVHHVNWCNGPGD54AFAKN7XCD/bundle.json","state_url":"https://pith.science/pith/IICVHHVNWCNGPGD54AFAKN7XCD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IICVHHVNWCNGPGD54AFAKN7XCD/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":"2026-08-09T14:32:39Z","links":{"resolver":"https://pith.science/pith/IICVHHVNWCNGPGD54AFAKN7XCD","bundle":"https://pith.science/pith/IICVHHVNWCNGPGD54AFAKN7XCD/bundle.json","state":"https://pith.science/pith/IICVHHVNWCNGPGD54AFAKN7XCD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IICVHHVNWCNGPGD54AFAKN7XCD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:IICVHHVNWCNGPGD54AFAKN7XCD","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":"2cf123ec06b2ab460ac282edd613aa83d56ede63008eba99dab9d707ebfeba9b","cross_cats_sorted":["cs.AI","cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-22T03:56:29Z","title_canon_sha256":"669c690ac5637dc03a4907e5e22e5b837bbc6c99454bfedfb958e353bca28c97"},"schema_version":"1.0","source":{"id":"2406.15723","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.15723","created_at":"2026-07-05T08:35:49Z"},{"alias_kind":"arxiv_version","alias_value":"2406.15723v1","created_at":"2026-07-05T08:35:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.15723","created_at":"2026-07-05T08:35:49Z"},{"alias_kind":"pith_short_12","alias_value":"IICVHHVNWCNG","created_at":"2026-07-05T08:35:49Z"},{"alias_kind":"pith_short_16","alias_value":"IICVHHVNWCNGPGD5","created_at":"2026-07-05T08:35:49Z"},{"alias_kind":"pith_short_8","alias_value":"IICVHHVN","created_at":"2026-07-05T08:35:49Z"}],"graph_snapshots":[{"event_id":"sha256:50ac7274211faf29d7051c7c7b49409b756b4d7d87dc451953669a0a98bd0803","target":"graph","created_at":"2026-07-05T08:35:49Z","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/2406.15723/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In automated pronunciation assessment, recent emphasis progressively lies on evaluating multiple aspects to provide enriched feedback. However, acquiring multi-aspect-score labeled data for non-native language learners' speech poses challenges; moreover, it often leads to score-imbalanced distributions. In this paper, we propose two Acoustic Feature Mixup strategies, linearly and non-linearly interpolating with the in-batch averaged feature, to address data scarcity and score-label imbalances. Primarily using goodness-of-pronunciation as an acoustic feature, we tailor mixup designs to suit pro","authors_text":"Gary Geunbae Lee, Heejin Do, Wonjun Lee","cross_cats":["cs.AI","cs.SD","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-22T03:56:29Z","title":"Acoustic Feature Mixup for Balanced Multi-aspect Pronunciation Assessment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.15723","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":"sha256:767d787f5502a3552a7c2a4ccca91742786f3111ff0546582a150ec981ca4d85","target":"record","created_at":"2026-07-05T08:35:49Z","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":"2cf123ec06b2ab460ac282edd613aa83d56ede63008eba99dab9d707ebfeba9b","cross_cats_sorted":["cs.AI","cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-22T03:56:29Z","title_canon_sha256":"669c690ac5637dc03a4907e5e22e5b837bbc6c99454bfedfb958e353bca28c97"},"schema_version":"1.0","source":{"id":"2406.15723","kind":"arxiv","version":1}},"canonical_sha256":"4205539eadb09a67987de00a0537f710d72ae341639d893c839f680d5fa189ec","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4205539eadb09a67987de00a0537f710d72ae341639d893c839f680d5fa189ec","first_computed_at":"2026-07-05T08:35:49.041378Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:35:49.041378Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JNZGkvOk9Z/EVD9/0tFPFNFthf6IImR2iyVKhiY/YiPvTJInQxAgwjldiMprrXY3AXNkxXHWsck/to5IXMdtDw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:35:49.041769Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.15723","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:767d787f5502a3552a7c2a4ccca91742786f3111ff0546582a150ec981ca4d85","sha256:50ac7274211faf29d7051c7c7b49409b756b4d7d87dc451953669a0a98bd0803"],"state_sha256":"dc270f535f26aaa6221cbaf1e8bf0835d4bc45600999ffb09d81de90d502cff0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tT57VgG0i+wc0+hgZPhOPDIsyy0xUg3mKEnQvX0ZKg0wwarP2ahv0kQxfdrdzBwan5Kx0ArOTrmE1OJVqsf2Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T14:32:39.228905Z","bundle_sha256":"a12f2de44c474c04eb2fed969117ef1ccd5e0fb32c3987594e4dfe12d316f2b5"}}