{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:NIQ6VF22DGYDWKMLFHFZTZ2TNG","short_pith_number":"pith:NIQ6VF22","canonical_record":{"source":{"id":"2205.09644","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-05-19T16:03:16Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"a392befc1b41d8e681a3062c62b00546f908f4e955cd604cbbb9cde939f14b63","abstract_canon_sha256":"fa11414b6a31d44b3295a61d270b20f944ca8260c12f8c9d0bb38388eec0b94e"},"schema_version":"1.0"},"canonical_sha256":"6a21ea975a19b03b298b29cb99e75369a5c6e8d8d083241a04a43aecbd253d9f","source":{"kind":"arxiv","id":"2205.09644","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.09644","created_at":"2026-07-05T06:16:00Z"},{"alias_kind":"arxiv_version","alias_value":"2205.09644v1","created_at":"2026-07-05T06:16:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.09644","created_at":"2026-07-05T06:16:00Z"},{"alias_kind":"pith_short_12","alias_value":"NIQ6VF22DGYD","created_at":"2026-07-05T06:16:00Z"},{"alias_kind":"pith_short_16","alias_value":"NIQ6VF22DGYDWKML","created_at":"2026-07-05T06:16:00Z"},{"alias_kind":"pith_short_8","alias_value":"NIQ6VF22","created_at":"2026-07-05T06:16:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:NIQ6VF22DGYDWKMLFHFZTZ2TNG","target":"record","payload":{"canonical_record":{"source":{"id":"2205.09644","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-05-19T16:03:16Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"a392befc1b41d8e681a3062c62b00546f908f4e955cd604cbbb9cde939f14b63","abstract_canon_sha256":"fa11414b6a31d44b3295a61d270b20f944ca8260c12f8c9d0bb38388eec0b94e"},"schema_version":"1.0"},"canonical_sha256":"6a21ea975a19b03b298b29cb99e75369a5c6e8d8d083241a04a43aecbd253d9f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:16:00.256779Z","signature_b64":"wkQBzzpHFrHT2KXllB+IzXdTfp2ZQsTmkqc2sLZklsYo2rofo/gzN+QZG0ph6XsFU8QHjVpqAeVE1NXroBSYAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6a21ea975a19b03b298b29cb99e75369a5c6e8d8d083241a04a43aecbd253d9f","last_reissued_at":"2026-07-05T06:16:00.256372Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:16:00.256372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.09644","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":"2026-07-05T06:16:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gR0QQNVGWbF3gkIw42d4qJD2GfKzFbN1QDOuvVnf1j/rQvIk1axt3Mz0qJ+lcP4L1+ZCiJxTYwZtw/KnC2U7Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T16:26:10.370522Z"},"content_sha256":"74ab0bb2aa48ca7acc837e55edb5998a58c955d74716fb4ebd7a028d0df3bebc","schema_version":"1.0","event_id":"sha256:74ab0bb2aa48ca7acc837e55edb5998a58c955d74716fb4ebd7a028d0df3bebc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:NIQ6VF22DGYDWKMLFHFZTZ2TNG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural network for multi-exponential sound energy decay analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Georg G\\\"otz, Ricardo Falc\\'on P\\'erez, Sebastian J. Schlecht, Ville Pulkki","submitted_at":"2022-05-19T16:03:16Z","abstract_excerpt":"An established model for sound energy decay functions (EDFs) is the superposition of multiple exponentials and a noise term. This work proposes a neural-network-based approach for estimating the model parameters from EDFs. The network is trained on synthetic EDFs and evaluated on two large datasets of over 20000 EDF measurements conducted in various acoustic environments. The evaluation shows that the proposed neural network architecture robustly estimates the model parameters from large datasets of measured EDFs, while being lightweight and computationally efficient. An implementation of the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.09644","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/2205.09644/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":"2026-07-05T06:16:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wxv8X9hpsMwyRziho8ZcPBlz2BjQEB4CXu30FnAcutx+3bCjuIp/1N0iIRC6+ZnFy5AkUGtOvTJW7bA7w5XkDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T16:26:10.370832Z"},"content_sha256":"9d103ca710eed725f349808ea7086a4ad714454c17c04c62212f27a7809310c8","schema_version":"1.0","event_id":"sha256:9d103ca710eed725f349808ea7086a4ad714454c17c04c62212f27a7809310c8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NIQ6VF22DGYDWKMLFHFZTZ2TNG/bundle.json","state_url":"https://pith.science/pith/NIQ6VF22DGYDWKMLFHFZTZ2TNG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NIQ6VF22DGYDWKMLFHFZTZ2TNG/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":"2026-08-14T16:26:10Z","links":{"resolver":"https://pith.science/pith/NIQ6VF22DGYDWKMLFHFZTZ2TNG","bundle":"https://pith.science/pith/NIQ6VF22DGYDWKMLFHFZTZ2TNG/bundle.json","state":"https://pith.science/pith/NIQ6VF22DGYDWKMLFHFZTZ2TNG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NIQ6VF22DGYDWKMLFHFZTZ2TNG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:NIQ6VF22DGYDWKMLFHFZTZ2TNG","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":"fa11414b6a31d44b3295a61d270b20f944ca8260c12f8c9d0bb38388eec0b94e","cross_cats_sorted":["cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-05-19T16:03:16Z","title_canon_sha256":"a392befc1b41d8e681a3062c62b00546f908f4e955cd604cbbb9cde939f14b63"},"schema_version":"1.0","source":{"id":"2205.09644","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.09644","created_at":"2026-07-05T06:16:00Z"},{"alias_kind":"arxiv_version","alias_value":"2205.09644v1","created_at":"2026-07-05T06:16:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.09644","created_at":"2026-07-05T06:16:00Z"},{"alias_kind":"pith_short_12","alias_value":"NIQ6VF22DGYD","created_at":"2026-07-05T06:16:00Z"},{"alias_kind":"pith_short_16","alias_value":"NIQ6VF22DGYDWKML","created_at":"2026-07-05T06:16:00Z"},{"alias_kind":"pith_short_8","alias_value":"NIQ6VF22","created_at":"2026-07-05T06:16:00Z"}],"graph_snapshots":[{"event_id":"sha256:9d103ca710eed725f349808ea7086a4ad714454c17c04c62212f27a7809310c8","target":"graph","created_at":"2026-07-05T06:16:00Z","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/2205.09644/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"An established model for sound energy decay functions (EDFs) is the superposition of multiple exponentials and a noise term. This work proposes a neural-network-based approach for estimating the model parameters from EDFs. The network is trained on synthetic EDFs and evaluated on two large datasets of over 20000 EDF measurements conducted in various acoustic environments. The evaluation shows that the proposed neural network architecture robustly estimates the model parameters from large datasets of measured EDFs, while being lightweight and computationally efficient. An implementation of the ","authors_text":"Georg G\\\"otz, Ricardo Falc\\'on P\\'erez, Sebastian J. Schlecht, Ville Pulkki","cross_cats":["cs.SD"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-05-19T16:03:16Z","title":"Neural network for multi-exponential sound energy decay analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.09644","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":"sha256:74ab0bb2aa48ca7acc837e55edb5998a58c955d74716fb4ebd7a028d0df3bebc","target":"record","created_at":"2026-07-05T06:16:00Z","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":"fa11414b6a31d44b3295a61d270b20f944ca8260c12f8c9d0bb38388eec0b94e","cross_cats_sorted":["cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2022-05-19T16:03:16Z","title_canon_sha256":"a392befc1b41d8e681a3062c62b00546f908f4e955cd604cbbb9cde939f14b63"},"schema_version":"1.0","source":{"id":"2205.09644","kind":"arxiv","version":1}},"canonical_sha256":"6a21ea975a19b03b298b29cb99e75369a5c6e8d8d083241a04a43aecbd253d9f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6a21ea975a19b03b298b29cb99e75369a5c6e8d8d083241a04a43aecbd253d9f","first_computed_at":"2026-07-05T06:16:00.256372Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:16:00.256372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wkQBzzpHFrHT2KXllB+IzXdTfp2ZQsTmkqc2sLZklsYo2rofo/gzN+QZG0ph6XsFU8QHjVpqAeVE1NXroBSYAg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:16:00.256779Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.09644","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:74ab0bb2aa48ca7acc837e55edb5998a58c955d74716fb4ebd7a028d0df3bebc","sha256:9d103ca710eed725f349808ea7086a4ad714454c17c04c62212f27a7809310c8"],"state_sha256":"f64deb7ab4a5c338e892f5606423eb63915411b54125e297d2860961f72c155d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r3tYRBWt4oEIDAmTj7SK2AmUIbvu83Z5bGIZ5Ey8K+WZ5QlxRlTCHkZw/T1a+Pckv0qaPtnYCuSrrBccJgaJBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T16:26:10.373663Z","bundle_sha256":"8953e6b84a3a85ac3174f5c58570c3ed66637ce0a950ae88c18b22b18ea884a1"}}