{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:LUVJNM4S3RJQ7ROYFS6YWOXTGP","short_pith_number":"pith:LUVJNM4S","schema_version":"1.0","canonical_sha256":"5d2a96b392dc530fc5d82cbd8b3af333e1b54cc88b2bb4c1a49fdb5f783b3733","source":{"kind":"arxiv","id":"1606.09163","version":1},"attestation_state":"computed","paper":{"title":"Optimising The Input Window Alignment in CD-DNN Based Phoneme Recognition for Low Latency Processing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.NE","stat.ML"],"primary_cat":"cs.CL","authors_text":"Akash Kumar Dhaka, Giampiero Salvi","submitted_at":"2016-06-29T15:51:44Z","abstract_excerpt":"We present a systematic analysis on the performance of a phonetic recogniser when the window of input features is not symmetric with respect to the current frame. The recogniser is based on Context Dependent Deep Neural Networks (CD-DNNs) and Hidden Markov Models (HMMs). The objective is to reduce the latency of the system by reducing the number of future feature frames required to estimate the current output. Our tests performed on the TIMIT database show that the performance does not degrade when the input window is shifted up to 5 frames in the past compared to common practice (no future fr"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1606.09163","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-29T15:51:44Z","cross_cats_sorted":["cs.CV","cs.NE","stat.ML"],"title_canon_sha256":"08690919086c5686ecc45e65811108f8bf87f6e8e0407975b067dcafd6773813","abstract_canon_sha256":"1ad946453897dda2f396afbc1604cdaa2747b3d11df55ae4f3dd4ceae23e31e3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:11:41.650041Z","signature_b64":"zJEB6RGi01V2lui7ebz5Gxzqu/kwlMDOhaOnlpOmX96eTKN+yxnuca0kSgBChuXW2Bsx7Ozd+2F35I/M/boqDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d2a96b392dc530fc5d82cbd8b3af333e1b54cc88b2bb4c1a49fdb5f783b3733","last_reissued_at":"2026-05-18T01:11:41.649706Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:11:41.649706Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimising The Input Window Alignment in CD-DNN Based Phoneme Recognition for Low Latency Processing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.NE","stat.ML"],"primary_cat":"cs.CL","authors_text":"Akash Kumar Dhaka, Giampiero Salvi","submitted_at":"2016-06-29T15:51:44Z","abstract_excerpt":"We present a systematic analysis on the performance of a phonetic recogniser when the window of input features is not symmetric with respect to the current frame. The recogniser is based on Context Dependent Deep Neural Networks (CD-DNNs) and Hidden Markov Models (HMMs). The objective is to reduce the latency of the system by reducing the number of future feature frames required to estimate the current output. Our tests performed on the TIMIT database show that the performance does not degrade when the input window is shifted up to 5 frames in the past compared to common practice (no future fr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.09163","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1606.09163","created_at":"2026-05-18T01:11:41.649762+00:00"},{"alias_kind":"arxiv_version","alias_value":"1606.09163v1","created_at":"2026-05-18T01:11:41.649762+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.09163","created_at":"2026-05-18T01:11:41.649762+00:00"},{"alias_kind":"pith_short_12","alias_value":"LUVJNM4S3RJQ","created_at":"2026-05-18T12:30:29.479603+00:00"},{"alias_kind":"pith_short_16","alias_value":"LUVJNM4S3RJQ7ROY","created_at":"2026-05-18T12:30:29.479603+00:00"},{"alias_kind":"pith_short_8","alias_value":"LUVJNM4S","created_at":"2026-05-18T12:30:29.479603+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/LUVJNM4S3RJQ7ROYFS6YWOXTGP","json":"https://pith.science/pith/LUVJNM4S3RJQ7ROYFS6YWOXTGP.json","graph_json":"https://pith.science/api/pith-number/LUVJNM4S3RJQ7ROYFS6YWOXTGP/graph.json","events_json":"https://pith.science/api/pith-number/LUVJNM4S3RJQ7ROYFS6YWOXTGP/events.json","paper":"https://pith.science/paper/LUVJNM4S"},"agent_actions":{"view_html":"https://pith.science/pith/LUVJNM4S3RJQ7ROYFS6YWOXTGP","download_json":"https://pith.science/pith/LUVJNM4S3RJQ7ROYFS6YWOXTGP.json","view_paper":"https://pith.science/paper/LUVJNM4S","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1606.09163&json=true","fetch_graph":"https://pith.science/api/pith-number/LUVJNM4S3RJQ7ROYFS6YWOXTGP/graph.json","fetch_events":"https://pith.science/api/pith-number/LUVJNM4S3RJQ7ROYFS6YWOXTGP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LUVJNM4S3RJQ7ROYFS6YWOXTGP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LUVJNM4S3RJQ7ROYFS6YWOXTGP/action/storage_attestation","attest_author":"https://pith.science/pith/LUVJNM4S3RJQ7ROYFS6YWOXTGP/action/author_attestation","sign_citation":"https://pith.science/pith/LUVJNM4S3RJQ7ROYFS6YWOXTGP/action/citation_signature","submit_replication":"https://pith.science/pith/LUVJNM4S3RJQ7ROYFS6YWOXTGP/action/replication_record"}},"created_at":"2026-05-18T01:11:41.649762+00:00","updated_at":"2026-05-18T01:11:41.649762+00:00"}