{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:UHEEB4IZS7WY4YRRBAFLGDPWZI","short_pith_number":"pith:UHEEB4IZ","canonical_record":{"source":{"id":"1808.08929","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.AS","submitted_at":"2018-08-27T17:05:50Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"fde729909e31643970d048e43b6e30adac35e57e63a4de584fa721b615d7c976","abstract_canon_sha256":"793d1ecbfcc2d13d590357080d2bd3caef2c4d2db4f98ceaf6ec5cad02fb94b5"},"schema_version":"1.0"},"canonical_sha256":"a1c840f11997ed8e6231080ab30df6ca2d8b4123e96e1d828d109e59201f473f","source":{"kind":"arxiv","id":"1808.08929","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.08929","created_at":"2026-05-18T00:07:12Z"},{"alias_kind":"arxiv_version","alias_value":"1808.08929v1","created_at":"2026-05-18T00:07:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.08929","created_at":"2026-05-18T00:07:12Z"},{"alias_kind":"pith_short_12","alias_value":"UHEEB4IZS7WY","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"UHEEB4IZS7WY4YRR","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"UHEEB4IZ","created_at":"2026-05-18T12:32:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:UHEEB4IZS7WY4YRRBAFLGDPWZI","target":"record","payload":{"canonical_record":{"source":{"id":"1808.08929","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.AS","submitted_at":"2018-08-27T17:05:50Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"fde729909e31643970d048e43b6e30adac35e57e63a4de584fa721b615d7c976","abstract_canon_sha256":"793d1ecbfcc2d13d590357080d2bd3caef2c4d2db4f98ceaf6ec5cad02fb94b5"},"schema_version":"1.0"},"canonical_sha256":"a1c840f11997ed8e6231080ab30df6ca2d8b4123e96e1d828d109e59201f473f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:07:12.791041Z","signature_b64":"v2kJllNZ67NflRL9F09g21nIAcAJtlLJYOGCrtOnOtUuQ2gB628hq0jGHBIrU+9P16K+e8RyF5XunX+49ZG+Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a1c840f11997ed8e6231080ab30df6ca2d8b4123e96e1d828d109e59201f473f","last_reissued_at":"2026-05-18T00:07:12.790496Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:07:12.790496Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.08929","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":"2026-05-18T00:07:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+MZLt8zcQmt4BA6JkPv5a+13HzsslFQ+WR8nKSBI8286lU86/7s+UQp/QAMabtqesCNy4o4h1lJ5YVPCYJ66Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T18:48:09.329781Z"},"content_sha256":"e0d43f060a5bd2b754fb367e9499e54f34b6d31ff41544b8dc2c9beb050e2c52","schema_version":"1.0","event_id":"sha256:e0d43f060a5bd2b754fb367e9499e54f34b6d31ff41544b8dc2c9beb050e2c52"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:UHEEB4IZS7WY4YRRBAFLGDPWZI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A neural attention model for speech command recognition","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Christoph Bernkopf, Douglas Coimbra de Andrade, Martin Loesener Da Silva Viana, Sabato Leo","submitted_at":"2018-08-27T17:05:50Z","abstract_excerpt":"This paper introduces a convolutional recurrent network with attention for speech command recognition. Attention models are powerful tools to improve performance on natural language, image captioning and speech tasks. The proposed model establishes a new state-of-the-art accuracy of 94.1% on Google Speech Commands dataset V1 and 94.5% on V2 (for the 20-commands recognition task), while still keeping a small footprint of only 202K trainable parameters. Results are compared with previous convolutional implementations on 5 different tasks (20 commands recognition (V1 and V2), 12 commands recognit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.08929","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":""},"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":"2026-05-18T00:07:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HBcGSqxIsSC4pn79WcW1YUHaZoY5aYUGc2tZySKvDmxU30COmA+fUGs2NikZni2qOtX/nvjNaHTQ1sse5rvVCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T18:48:09.330170Z"},"content_sha256":"835f46db5652bf5a27c55a5aad834ff599ee37b153b17fbbf05e9a82049e5413","schema_version":"1.0","event_id":"sha256:835f46db5652bf5a27c55a5aad834ff599ee37b153b17fbbf05e9a82049e5413"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UHEEB4IZS7WY4YRRBAFLGDPWZI/bundle.json","state_url":"https://pith.science/pith/UHEEB4IZS7WY4YRRBAFLGDPWZI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UHEEB4IZS7WY4YRRBAFLGDPWZI/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":"2026-05-25T18:48:09Z","links":{"resolver":"https://pith.science/pith/UHEEB4IZS7WY4YRRBAFLGDPWZI","bundle":"https://pith.science/pith/UHEEB4IZS7WY4YRRBAFLGDPWZI/bundle.json","state":"https://pith.science/pith/UHEEB4IZS7WY4YRRBAFLGDPWZI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UHEEB4IZS7WY4YRRBAFLGDPWZI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:UHEEB4IZS7WY4YRRBAFLGDPWZI","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":"793d1ecbfcc2d13d590357080d2bd3caef2c4d2db4f98ceaf6ec5cad02fb94b5","cross_cats_sorted":["cs.SD"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.AS","submitted_at":"2018-08-27T17:05:50Z","title_canon_sha256":"fde729909e31643970d048e43b6e30adac35e57e63a4de584fa721b615d7c976"},"schema_version":"1.0","source":{"id":"1808.08929","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.08929","created_at":"2026-05-18T00:07:12Z"},{"alias_kind":"arxiv_version","alias_value":"1808.08929v1","created_at":"2026-05-18T00:07:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.08929","created_at":"2026-05-18T00:07:12Z"},{"alias_kind":"pith_short_12","alias_value":"UHEEB4IZS7WY","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"UHEEB4IZS7WY4YRR","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"UHEEB4IZ","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:835f46db5652bf5a27c55a5aad834ff599ee37b153b17fbbf05e9a82049e5413","target":"graph","created_at":"2026-05-18T00:07:12Z","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"},"paper":{"abstract_excerpt":"This paper introduces a convolutional recurrent network with attention for speech command recognition. Attention models are powerful tools to improve performance on natural language, image captioning and speech tasks. The proposed model establishes a new state-of-the-art accuracy of 94.1% on Google Speech Commands dataset V1 and 94.5% on V2 (for the 20-commands recognition task), while still keeping a small footprint of only 202K trainable parameters. Results are compared with previous convolutional implementations on 5 different tasks (20 commands recognition (V1 and V2), 12 commands recognit","authors_text":"Christoph Bernkopf, Douglas Coimbra de Andrade, Martin Loesener Da Silva Viana, Sabato Leo","cross_cats":["cs.SD"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.AS","submitted_at":"2018-08-27T17:05:50Z","title":"A neural attention model for speech command recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.08929","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:e0d43f060a5bd2b754fb367e9499e54f34b6d31ff41544b8dc2c9beb050e2c52","target":"record","created_at":"2026-05-18T00:07:12Z","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":"793d1ecbfcc2d13d590357080d2bd3caef2c4d2db4f98ceaf6ec5cad02fb94b5","cross_cats_sorted":["cs.SD"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.AS","submitted_at":"2018-08-27T17:05:50Z","title_canon_sha256":"fde729909e31643970d048e43b6e30adac35e57e63a4de584fa721b615d7c976"},"schema_version":"1.0","source":{"id":"1808.08929","kind":"arxiv","version":1}},"canonical_sha256":"a1c840f11997ed8e6231080ab30df6ca2d8b4123e96e1d828d109e59201f473f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a1c840f11997ed8e6231080ab30df6ca2d8b4123e96e1d828d109e59201f473f","first_computed_at":"2026-05-18T00:07:12.790496Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:07:12.790496Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"v2kJllNZ67NflRL9F09g21nIAcAJtlLJYOGCrtOnOtUuQ2gB628hq0jGHBIrU+9P16K+e8RyF5XunX+49ZG+Bg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:07:12.791041Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.08929","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e0d43f060a5bd2b754fb367e9499e54f34b6d31ff41544b8dc2c9beb050e2c52","sha256:835f46db5652bf5a27c55a5aad834ff599ee37b153b17fbbf05e9a82049e5413"],"state_sha256":"e9d3d0dbe12e546320ed45d562a40c6a1a87b1ec777975c9d0b65b08265dc289"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5njYyWd+0Zpk47XI7fH4+uS78pLml3MoGZZXv001ildA9ApT3qQuVMCjJ+Vgx5jESsC+r6U3oObqUhdpkU6dCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T18:48:09.333584Z","bundle_sha256":"0498cfe74fea69af1efa0c4de49452a96ec946cde0125cf8117922c967eaf1bd"}}