{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SQOZQH2RFCXYTOB5F2XLPLTECM","short_pith_number":"pith:SQOZQH2R","canonical_record":{"source":{"id":"2412.08306","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-12-11T11:36:24Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"2642434505542e387dfc094e4cfb9759e6a871ea1608ba0e4463cee5d28385fa","abstract_canon_sha256":"8bb48b0ceaa2787e6a430d33ad5a031f707e5ad74d9ae27b6dd0555c792e7ff9"},"schema_version":"1.0"},"canonical_sha256":"941d981f5128af89b83d2eaeb7ae641318af5a46f3f8e64fe980deba21433355","source":{"kind":"arxiv","id":"2412.08306","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.08306","created_at":"2026-07-05T09:47:48Z"},{"alias_kind":"arxiv_version","alias_value":"2412.08306v1","created_at":"2026-07-05T09:47:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.08306","created_at":"2026-07-05T09:47:48Z"},{"alias_kind":"pith_short_12","alias_value":"SQOZQH2RFCXY","created_at":"2026-07-05T09:47:48Z"},{"alias_kind":"pith_short_16","alias_value":"SQOZQH2RFCXYTOB5","created_at":"2026-07-05T09:47:48Z"},{"alias_kind":"pith_short_8","alias_value":"SQOZQH2R","created_at":"2026-07-05T09:47:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SQOZQH2RFCXYTOB5F2XLPLTECM","target":"record","payload":{"canonical_record":{"source":{"id":"2412.08306","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-12-11T11:36:24Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"2642434505542e387dfc094e4cfb9759e6a871ea1608ba0e4463cee5d28385fa","abstract_canon_sha256":"8bb48b0ceaa2787e6a430d33ad5a031f707e5ad74d9ae27b6dd0555c792e7ff9"},"schema_version":"1.0"},"canonical_sha256":"941d981f5128af89b83d2eaeb7ae641318af5a46f3f8e64fe980deba21433355","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:47:48.045443Z","signature_b64":"uUhn8LxNQoxyn+nBKZyun57MrVV0BnbNwhtZy8AeHjfh//Oh/yQH3zI5Piv4A6Epx3zXpF03jdCSZmdQkiFlDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"941d981f5128af89b83d2eaeb7ae641318af5a46f3f8e64fe980deba21433355","last_reissued_at":"2026-07-05T09:47:48.045065Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:47:48.045065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.08306","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":"2026-07-05T09:47:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g149qpIe5nix/C62JKN79mxzfHTzhneUCKoC5yhyc7FTZlJSax84Pt3ReRL5DbvKXAJzWrdwbB/GhonpSbWZAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T17:40:41.986036Z"},"content_sha256":"303e200fe94154c050e9cfae5fcfaadd696d1c7d7635f9db8c299ee000a9b3f3","schema_version":"1.0","event_id":"sha256:303e200fe94154c050e9cfae5fcfaadd696d1c7d7635f9db8c299ee000a9b3f3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SQOZQH2RFCXYTOB5F2XLPLTECM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evaluating the Impact of Discriminative and Generative E2E Speech Enhancement Models on Syllable Stress Preservation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Chiranjeevi Yarra, Jhansi Mallela, Rangavajjala Sankara Bharadwaj, Sai Harshitha Aluru","submitted_at":"2024-12-11T11:36:24Z","abstract_excerpt":"Automatic syllable stress detection is a crucial component in Computer-Assisted Language Learning (CALL) systems for language learners. Current stress detection models are typically trained on clean speech, which may not be robust in real-world scenarios where background noise is prevalent. To address this, speech enhancement (SE) models, designed to enhance speech by removing noise, might be employed, but their impact on preserving syllable stress patterns is not well studied. This study examines how different SE models, representing discriminative and generative modeling approaches, affect s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.08306","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/2412.08306/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":"2026-07-05T09:47:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y5yW8diSDnc3YD1zqd9kknB+57bcntz+K0iJqiTnwRnT+N0xVlfCYsK/f8K8uYAG+YxDpc1ET+u22RWJ9mIRDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T17:40:41.986540Z"},"content_sha256":"c0dc2b692076c09b533f60953a04ee97855200a5036ab3988b0fca3c926c2c45","schema_version":"1.0","event_id":"sha256:c0dc2b692076c09b533f60953a04ee97855200a5036ab3988b0fca3c926c2c45"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SQOZQH2RFCXYTOB5F2XLPLTECM/bundle.json","state_url":"https://pith.science/pith/SQOZQH2RFCXYTOB5F2XLPLTECM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SQOZQH2RFCXYTOB5F2XLPLTECM/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":"2026-08-13T17:40:41Z","links":{"resolver":"https://pith.science/pith/SQOZQH2RFCXYTOB5F2XLPLTECM","bundle":"https://pith.science/pith/SQOZQH2RFCXYTOB5F2XLPLTECM/bundle.json","state":"https://pith.science/pith/SQOZQH2RFCXYTOB5F2XLPLTECM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SQOZQH2RFCXYTOB5F2XLPLTECM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SQOZQH2RFCXYTOB5F2XLPLTECM","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":"8bb48b0ceaa2787e6a430d33ad5a031f707e5ad74d9ae27b6dd0555c792e7ff9","cross_cats_sorted":["cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-12-11T11:36:24Z","title_canon_sha256":"2642434505542e387dfc094e4cfb9759e6a871ea1608ba0e4463cee5d28385fa"},"schema_version":"1.0","source":{"id":"2412.08306","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.08306","created_at":"2026-07-05T09:47:48Z"},{"alias_kind":"arxiv_version","alias_value":"2412.08306v1","created_at":"2026-07-05T09:47:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.08306","created_at":"2026-07-05T09:47:48Z"},{"alias_kind":"pith_short_12","alias_value":"SQOZQH2RFCXY","created_at":"2026-07-05T09:47:48Z"},{"alias_kind":"pith_short_16","alias_value":"SQOZQH2RFCXYTOB5","created_at":"2026-07-05T09:47:48Z"},{"alias_kind":"pith_short_8","alias_value":"SQOZQH2R","created_at":"2026-07-05T09:47:48Z"}],"graph_snapshots":[{"event_id":"sha256:c0dc2b692076c09b533f60953a04ee97855200a5036ab3988b0fca3c926c2c45","target":"graph","created_at":"2026-07-05T09:47:48Z","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/2412.08306/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automatic syllable stress detection is a crucial component in Computer-Assisted Language Learning (CALL) systems for language learners. Current stress detection models are typically trained on clean speech, which may not be robust in real-world scenarios where background noise is prevalent. To address this, speech enhancement (SE) models, designed to enhance speech by removing noise, might be employed, but their impact on preserving syllable stress patterns is not well studied. This study examines how different SE models, representing discriminative and generative modeling approaches, affect s","authors_text":"Chiranjeevi Yarra, Jhansi Mallela, Rangavajjala Sankara Bharadwaj, Sai Harshitha Aluru","cross_cats":["cs.SD"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-12-11T11:36:24Z","title":"Evaluating the Impact of Discriminative and Generative E2E Speech Enhancement Models on Syllable Stress Preservation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.08306","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":"sha256:303e200fe94154c050e9cfae5fcfaadd696d1c7d7635f9db8c299ee000a9b3f3","target":"record","created_at":"2026-07-05T09:47:48Z","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":"8bb48b0ceaa2787e6a430d33ad5a031f707e5ad74d9ae27b6dd0555c792e7ff9","cross_cats_sorted":["cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-12-11T11:36:24Z","title_canon_sha256":"2642434505542e387dfc094e4cfb9759e6a871ea1608ba0e4463cee5d28385fa"},"schema_version":"1.0","source":{"id":"2412.08306","kind":"arxiv","version":1}},"canonical_sha256":"941d981f5128af89b83d2eaeb7ae641318af5a46f3f8e64fe980deba21433355","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"941d981f5128af89b83d2eaeb7ae641318af5a46f3f8e64fe980deba21433355","first_computed_at":"2026-07-05T09:47:48.045065Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:47:48.045065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uUhn8LxNQoxyn+nBKZyun57MrVV0BnbNwhtZy8AeHjfh//Oh/yQH3zI5Piv4A6Epx3zXpF03jdCSZmdQkiFlDw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:47:48.045443Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.08306","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:303e200fe94154c050e9cfae5fcfaadd696d1c7d7635f9db8c299ee000a9b3f3","sha256:c0dc2b692076c09b533f60953a04ee97855200a5036ab3988b0fca3c926c2c45"],"state_sha256":"619a08bbcf35c038be842b34b6925f4675af9e95d7f54098556a50e742af5569"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bFYYxaU6mBwAdgkcdR7gbvrlawEojrH4PstwD0teM72XT1xdGkGsRtojs/Avw/rka1JBQSz0g3Ije4DZCeLvBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T17:40:41.990879Z","bundle_sha256":"2058879b80f3b4b15ff43da39ec611212a8acda5805c83451da3195b859bc952"}}