{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:W36G2JNC7PXS7NZW6HBYLPMHT4","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":"2875cc6eb08637b665aca3917bb0e91bf1dc7b69a82d718a4a8da8998a5d921c","cross_cats_sorted":["eess.AS","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-12-09T20:58:39Z","title_canon_sha256":"02373fb07c73166ab29318cf217d01ce3ca775df875e7a24aed71420bf9ee7bf"},"schema_version":"1.0","source":{"id":"1712.03439","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.03439","created_at":"2026-05-17T23:57:07Z"},{"alias_kind":"arxiv_version","alias_value":"1712.03439v2","created_at":"2026-05-17T23:57:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.03439","created_at":"2026-05-17T23:57:07Z"},{"alias_kind":"pith_short_12","alias_value":"W36G2JNC7PXS","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"W36G2JNC7PXS7NZW","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"W36G2JNC","created_at":"2026-05-18T12:31:49Z"}],"graph_snapshots":[{"event_id":"sha256:9c0a8b43e389b8c5ca75254270d9105c06742c9ab88c37022dd2b53512c1a66a","target":"graph","created_at":"2026-05-17T23:57:07Z","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":"In this paper, we describe how to efficiently implement an acoustic room simulator to generate large-scale simulated data for training deep neural networks. Even though Google Room Simulator in [1] was shown to be quite effective in reducing the Word Error Rates (WERs) for far-field applications by generating simulated far-field training sets, it requires a very large number of Fast Fourier Transforms (FFTs) of large size. Room Simulator in [1] used approximately 80 percent of Central Processing Unit (CPU) usage in our CPU + Graphics Processing Unit (GPU) training architecture [2]. In this wor","authors_text":"Arun Narayanan, Chanwoo Kim, Ehsan Variani, Michiel Bacchiani","cross_cats":["eess.AS","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-12-09T20:58:39Z","title":"Efficient Implementation of the Room Simulator for Training Deep Neural Network Acoustic Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.03439","kind":"arxiv","version":2},"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:df663161797bee1da7cff6601c7ec89aa98ff065196c694e5c4cc347826a6314","target":"record","created_at":"2026-05-17T23:57:07Z","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":"2875cc6eb08637b665aca3917bb0e91bf1dc7b69a82d718a4a8da8998a5d921c","cross_cats_sorted":["eess.AS","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-12-09T20:58:39Z","title_canon_sha256":"02373fb07c73166ab29318cf217d01ce3ca775df875e7a24aed71420bf9ee7bf"},"schema_version":"1.0","source":{"id":"1712.03439","kind":"arxiv","version":2}},"canonical_sha256":"b6fc6d25a2fbef2fb736f1c385bd879f10bf390bd95978a92a6219c4e2b8299d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b6fc6d25a2fbef2fb736f1c385bd879f10bf390bd95978a92a6219c4e2b8299d","first_computed_at":"2026-05-17T23:57:07.750557Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:57:07.750557Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"09ImQftMw9CZvp1pBX+SoLK5qFvVilvxAd03gRF6aLDo5P8X+f9qhi6JVmcqUsuCIRhxeTyyk7mB9p/tkDS6DQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:57:07.750978Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.03439","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:df663161797bee1da7cff6601c7ec89aa98ff065196c694e5c4cc347826a6314","sha256:9c0a8b43e389b8c5ca75254270d9105c06742c9ab88c37022dd2b53512c1a66a"],"state_sha256":"2b7570792f04382fc12fa66489dddfc7c7cd0ff9244aea0b6386fbdb9aa05bfe"}