{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:T4MO5FYKDCWLSAOXT6M6GZGPPD","short_pith_number":"pith:T4MO5FYK","canonical_record":{"source":{"id":"2607.16803","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2026-07-18T12:50:33Z","cross_cats_sorted":["cs.AI","cs.ET","cs.LG"],"title_canon_sha256":"f77827093f409f0b0e655af0d941fa96b8c7d76823011e3ac56acb9d1a5dfef8","abstract_canon_sha256":"77d32467539797c0f752062bf930debb3fc0ebdf9b807d7e9c5ac2dedffce0cf"},"schema_version":"1.0"},"canonical_sha256":"9f18ee970a18acb901d79f99e364cf78d2040a80d1cd169f371b789f29782e33","source":{"kind":"arxiv","id":"2607.16803","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.16803","created_at":"2026-07-21T01:20:59Z"},{"alias_kind":"arxiv_version","alias_value":"2607.16803v1","created_at":"2026-07-21T01:20:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.16803","created_at":"2026-07-21T01:20:59Z"},{"alias_kind":"pith_short_12","alias_value":"T4MO5FYKDCWL","created_at":"2026-07-21T01:20:59Z"},{"alias_kind":"pith_short_16","alias_value":"T4MO5FYKDCWLSAOX","created_at":"2026-07-21T01:20:59Z"},{"alias_kind":"pith_short_8","alias_value":"T4MO5FYK","created_at":"2026-07-21T01:20:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:T4MO5FYKDCWLSAOXT6M6GZGPPD","target":"record","payload":{"canonical_record":{"source":{"id":"2607.16803","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2026-07-18T12:50:33Z","cross_cats_sorted":["cs.AI","cs.ET","cs.LG"],"title_canon_sha256":"f77827093f409f0b0e655af0d941fa96b8c7d76823011e3ac56acb9d1a5dfef8","abstract_canon_sha256":"77d32467539797c0f752062bf930debb3fc0ebdf9b807d7e9c5ac2dedffce0cf"},"schema_version":"1.0"},"canonical_sha256":"9f18ee970a18acb901d79f99e364cf78d2040a80d1cd169f371b789f29782e33","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-21T01:20:59.653472Z","signature_b64":"vpC2UuQxm+Ak7KR2CKbCCFkpBTqOsWzTAtfLq2LRACMaRzVbSHSGo3tUXQftW/wnpfCFz5riGR6E2A6xW8i0Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9f18ee970a18acb901d79f99e364cf78d2040a80d1cd169f371b789f29782e33","last_reissued_at":"2026-07-21T01:20:59.652641Z","signature_status":"signed_v1","first_computed_at":"2026-07-21T01:20:59.652641Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.16803","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":"2026-07-21T01:20:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HLTJ9TVoIU+KB0cO/cCZA6HGKqgKIQZqx1qY5Mag63shlb8+OA/WlPu2CbwaoeTpTsqd7hYu5X5hAHw6Q3giBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T05:49:57.382230Z"},"content_sha256":"bd901db3dfffa427fca469c512d8897047a9247baa9a307bc69359ef7c98875e","schema_version":"1.0","event_id":"sha256:bd901db3dfffa427fca469c512d8897047a9247baa9a307bc69359ef7c98875e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:T4MO5FYKDCWLSAOXT6M6GZGPPD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Explainable Lightweight Compact Deep Models for Speech Emotion Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.ET","cs.LG"],"primary_cat":"cs.SD","authors_text":"Nelly Elsayed","submitted_at":"2026-07-18T12:50:33Z","abstract_excerpt":"Speech Emotion Recognition (SER) is an important component in a wide range of human-centered applications, including healthcare, customer service, and human-omputer interaction. In medical and decision-support settings, there is increasing interest in models that not only achieve accurate emotion recognition but also support transparent predictions and efficient deployment. However, many existing SER approaches rely on complex deep learning architectures that limit interpretability and increase computational cost. This paper presents an explainable and lightweight speech emotion recognition fr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.16803","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/2607.16803/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":"2026-07-21T01:20:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8ykGnx/lNu+KpR6l2Vm+H9FrJX8LG2y47djRyaEvuQSimQNOetuea9FnXXqzjO3WgxW7P5tUHNP0iyLbyxKbDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T05:49:57.382764Z"},"content_sha256":"063e16f6fb432e0eb0ff0a7b297d9fdaaafb0ae7ee9aaa35c37444c2593f8f1d","schema_version":"1.0","event_id":"sha256:063e16f6fb432e0eb0ff0a7b297d9fdaaafb0ae7ee9aaa35c37444c2593f8f1d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/T4MO5FYKDCWLSAOXT6M6GZGPPD/bundle.json","state_url":"https://pith.science/pith/T4MO5FYKDCWLSAOXT6M6GZGPPD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/T4MO5FYKDCWLSAOXT6M6GZGPPD/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":"2026-08-07T05:49:57Z","links":{"resolver":"https://pith.science/pith/T4MO5FYKDCWLSAOXT6M6GZGPPD","bundle":"https://pith.science/pith/T4MO5FYKDCWLSAOXT6M6GZGPPD/bundle.json","state":"https://pith.science/pith/T4MO5FYKDCWLSAOXT6M6GZGPPD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/T4MO5FYKDCWLSAOXT6M6GZGPPD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:T4MO5FYKDCWLSAOXT6M6GZGPPD","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":"77d32467539797c0f752062bf930debb3fc0ebdf9b807d7e9c5ac2dedffce0cf","cross_cats_sorted":["cs.AI","cs.ET","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2026-07-18T12:50:33Z","title_canon_sha256":"f77827093f409f0b0e655af0d941fa96b8c7d76823011e3ac56acb9d1a5dfef8"},"schema_version":"1.0","source":{"id":"2607.16803","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.16803","created_at":"2026-07-21T01:20:59Z"},{"alias_kind":"arxiv_version","alias_value":"2607.16803v1","created_at":"2026-07-21T01:20:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.16803","created_at":"2026-07-21T01:20:59Z"},{"alias_kind":"pith_short_12","alias_value":"T4MO5FYKDCWL","created_at":"2026-07-21T01:20:59Z"},{"alias_kind":"pith_short_16","alias_value":"T4MO5FYKDCWLSAOX","created_at":"2026-07-21T01:20:59Z"},{"alias_kind":"pith_short_8","alias_value":"T4MO5FYK","created_at":"2026-07-21T01:20:59Z"}],"graph_snapshots":[{"event_id":"sha256:063e16f6fb432e0eb0ff0a7b297d9fdaaafb0ae7ee9aaa35c37444c2593f8f1d","target":"graph","created_at":"2026-07-21T01:20:59Z","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/2607.16803/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Speech Emotion Recognition (SER) is an important component in a wide range of human-centered applications, including healthcare, customer service, and human-omputer interaction. In medical and decision-support settings, there is increasing interest in models that not only achieve accurate emotion recognition but also support transparent predictions and efficient deployment. However, many existing SER approaches rely on complex deep learning architectures that limit interpretability and increase computational cost. This paper presents an explainable and lightweight speech emotion recognition fr","authors_text":"Nelly Elsayed","cross_cats":["cs.AI","cs.ET","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2026-07-18T12:50:33Z","title":"Explainable Lightweight Compact Deep Models for Speech Emotion Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.16803","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:bd901db3dfffa427fca469c512d8897047a9247baa9a307bc69359ef7c98875e","target":"record","created_at":"2026-07-21T01:20:59Z","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":"77d32467539797c0f752062bf930debb3fc0ebdf9b807d7e9c5ac2dedffce0cf","cross_cats_sorted":["cs.AI","cs.ET","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2026-07-18T12:50:33Z","title_canon_sha256":"f77827093f409f0b0e655af0d941fa96b8c7d76823011e3ac56acb9d1a5dfef8"},"schema_version":"1.0","source":{"id":"2607.16803","kind":"arxiv","version":1}},"canonical_sha256":"9f18ee970a18acb901d79f99e364cf78d2040a80d1cd169f371b789f29782e33","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9f18ee970a18acb901d79f99e364cf78d2040a80d1cd169f371b789f29782e33","first_computed_at":"2026-07-21T01:20:59.652641Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-21T01:20:59.652641Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vpC2UuQxm+Ak7KR2CKbCCFkpBTqOsWzTAtfLq2LRACMaRzVbSHSGo3tUXQftW/wnpfCFz5riGR6E2A6xW8i0Aw==","signature_status":"signed_v1","signed_at":"2026-07-21T01:20:59.653472Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.16803","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bd901db3dfffa427fca469c512d8897047a9247baa9a307bc69359ef7c98875e","sha256:063e16f6fb432e0eb0ff0a7b297d9fdaaafb0ae7ee9aaa35c37444c2593f8f1d"],"state_sha256":"2d5e426beba54658f9ffbacc2c796ddc725b5598341e56ce8ad00b80de3517e2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+ZpMfFeqIapfTr4HTMhg+NEvFAjdXbzs0SsZyVXXXtnAeTNl9JDO7V46ZfVp3CskJY6OZhDrah2CR0jxDCa2Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T05:49:57.386494Z","bundle_sha256":"0ad93d943e7fa0e26f273e26aae09e9278de1d5e44417113849eac5776024899"}}