{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:TRUAV6I66DEPQW3F6NSZF4MXUQ","short_pith_number":"pith:TRUAV6I6","schema_version":"1.0","canonical_sha256":"9c680af91ef0c8f85b65f36592f197a40ae62bc321de777dc98fe6ad252b187f","source":{"kind":"arxiv","id":"1811.07453","version":2},"attestation_state":"computed","paper":{"title":"The PyTorch-Kaldi Speech Recognition Toolkit","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.LG","cs.NE"],"primary_cat":"eess.AS","authors_text":"Mirco Ravanelli, Titouan Parcollet, Yoshua Bengio","submitted_at":"2018-11-19T01:57:05Z","abstract_excerpt":"The availability of open-source software is playing a remarkable role in the popularization of speech recognition and deep learning. Kaldi, for instance, is nowadays an established framework used to develop state-of-the-art speech recognizers. PyTorch is used to build neural networks with the Python language and has recently spawn tremendous interest within the machine learning community thanks to its simplicity and flexibility.\n  The PyTorch-Kaldi project aims to bridge the gap between these popular toolkits, trying to inherit the efficiency of Kaldi and the flexibility of PyTorch. PyTorch-Ka"},"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":"1811.07453","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2018-11-19T01:57:05Z","cross_cats_sorted":["cs.CL","cs.LG","cs.NE"],"title_canon_sha256":"5cdcaf3b5b01692e24eb939b3ebcf8f98f7f72ad9e5fb1fea4ccb5ef69256310","abstract_canon_sha256":"84b1a157fd0d34c761f3cfd6b0273aa6e07e4ecffb3b36f16daf7988c1af3ae8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:53:50.170834Z","signature_b64":"3mfO/UqJL9Q8SQLOejVoEXf6wxg88Zf5o3UTtfpCf9tVZPsT4gdXpS/4e5gfQ5GcYsEDQI+y65AzYxH4sAlBAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c680af91ef0c8f85b65f36592f197a40ae62bc321de777dc98fe6ad252b187f","last_reissued_at":"2026-05-17T23:53:50.170039Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:53:50.170039Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The PyTorch-Kaldi Speech Recognition Toolkit","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.LG","cs.NE"],"primary_cat":"eess.AS","authors_text":"Mirco Ravanelli, Titouan Parcollet, Yoshua Bengio","submitted_at":"2018-11-19T01:57:05Z","abstract_excerpt":"The availability of open-source software is playing a remarkable role in the popularization of speech recognition and deep learning. Kaldi, for instance, is nowadays an established framework used to develop state-of-the-art speech recognizers. PyTorch is used to build neural networks with the Python language and has recently spawn tremendous interest within the machine learning community thanks to its simplicity and flexibility.\n  The PyTorch-Kaldi project aims to bridge the gap between these popular toolkits, trying to inherit the efficiency of Kaldi and the flexibility of PyTorch. PyTorch-Ka"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.07453","kind":"arxiv","version":2},"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":"1811.07453","created_at":"2026-05-17T23:53:50.170188+00:00"},{"alias_kind":"arxiv_version","alias_value":"1811.07453v2","created_at":"2026-05-17T23:53:50.170188+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.07453","created_at":"2026-05-17T23:53:50.170188+00:00"},{"alias_kind":"pith_short_12","alias_value":"TRUAV6I66DEP","created_at":"2026-05-18T12:32:56.356000+00:00"},{"alias_kind":"pith_short_16","alias_value":"TRUAV6I66DEPQW3F","created_at":"2026-05-18T12:32:56.356000+00:00"},{"alias_kind":"pith_short_8","alias_value":"TRUAV6I6","created_at":"2026-05-18T12:32:56.356000+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/TRUAV6I66DEPQW3F6NSZF4MXUQ","json":"https://pith.science/pith/TRUAV6I66DEPQW3F6NSZF4MXUQ.json","graph_json":"https://pith.science/api/pith-number/TRUAV6I66DEPQW3F6NSZF4MXUQ/graph.json","events_json":"https://pith.science/api/pith-number/TRUAV6I66DEPQW3F6NSZF4MXUQ/events.json","paper":"https://pith.science/paper/TRUAV6I6"},"agent_actions":{"view_html":"https://pith.science/pith/TRUAV6I66DEPQW3F6NSZF4MXUQ","download_json":"https://pith.science/pith/TRUAV6I66DEPQW3F6NSZF4MXUQ.json","view_paper":"https://pith.science/paper/TRUAV6I6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1811.07453&json=true","fetch_graph":"https://pith.science/api/pith-number/TRUAV6I66DEPQW3F6NSZF4MXUQ/graph.json","fetch_events":"https://pith.science/api/pith-number/TRUAV6I66DEPQW3F6NSZF4MXUQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TRUAV6I66DEPQW3F6NSZF4MXUQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TRUAV6I66DEPQW3F6NSZF4MXUQ/action/storage_attestation","attest_author":"https://pith.science/pith/TRUAV6I66DEPQW3F6NSZF4MXUQ/action/author_attestation","sign_citation":"https://pith.science/pith/TRUAV6I66DEPQW3F6NSZF4MXUQ/action/citation_signature","submit_replication":"https://pith.science/pith/TRUAV6I66DEPQW3F6NSZF4MXUQ/action/replication_record"}},"created_at":"2026-05-17T23:53:50.170188+00:00","updated_at":"2026-05-17T23:53:50.170188+00:00"}