{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:SDPKTVVE4JJDDDAV3DNAHUKL67","short_pith_number":"pith:SDPKTVVE","schema_version":"1.0","canonical_sha256":"90dea9d6a4e252318c15d8da03d14bf7e0e03804c87482508aa97fcf06bf6f09","source":{"kind":"arxiv","id":"2109.13673","version":1},"attestation_state":"computed","paper":{"title":"Nana-HDR: A Non-attentive Non-autoregressive Hybrid Model for TTS","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SD","eess.AS"],"primary_cat":"cs.CL","authors_text":"Fenglong Xie, Li Lu, Li Meng, Shilun Lin, Wenchao Su, Xinhui Li","submitted_at":"2021-09-28T12:45:14Z","abstract_excerpt":"This paper presents Nana-HDR, a new non-attentive non-autoregressive model with hybrid Transformer-based Dense-fuse encoder and RNN-based decoder for TTS. It mainly consists of three parts: Firstly, a novel Dense-fuse encoder with dense connections between basic Transformer blocks for coarse feature fusion and a multi-head attention layer for fine feature fusion. Secondly, a single-layer non-autoregressive RNN-based decoder. Thirdly, a duration predictor instead of an attention model that connects the above hybrid encoder and decoder. Experiments indicate that Nana-HDR gives full play to the a"},"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":"2109.13673","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-09-28T12:45:14Z","cross_cats_sorted":["cs.SD","eess.AS"],"title_canon_sha256":"a4fca922b39b4fe7a1f258b0ba01483e72877c33efe4cb49aa6a9813329de500","abstract_canon_sha256":"3cb7aa301e9108a7008b2998618f15bef75c1b390dc69fc7392d4fd0428551a1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:18:05.301560Z","signature_b64":"Br2gzrUx169SWnP0O/uX54dIcRQwoHpyzWIvANV6yXP3MdL75XAa3muz2zCkWq2W3qCWPa1EjIIy8Z25KwEuAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"90dea9d6a4e252318c15d8da03d14bf7e0e03804c87482508aa97fcf06bf6f09","last_reissued_at":"2026-07-05T03:18:05.301162Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:18:05.301162Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Nana-HDR: A Non-attentive Non-autoregressive Hybrid Model for TTS","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SD","eess.AS"],"primary_cat":"cs.CL","authors_text":"Fenglong Xie, Li Lu, Li Meng, Shilun Lin, Wenchao Su, Xinhui Li","submitted_at":"2021-09-28T12:45:14Z","abstract_excerpt":"This paper presents Nana-HDR, a new non-attentive non-autoregressive model with hybrid Transformer-based Dense-fuse encoder and RNN-based decoder for TTS. It mainly consists of three parts: Firstly, a novel Dense-fuse encoder with dense connections between basic Transformer blocks for coarse feature fusion and a multi-head attention layer for fine feature fusion. Secondly, a single-layer non-autoregressive RNN-based decoder. Thirdly, a duration predictor instead of an attention model that connects the above hybrid encoder and decoder. Experiments indicate that Nana-HDR gives full play to the a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.13673","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/2109.13673/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2109.13673","created_at":"2026-07-05T03:18:05.301228+00:00"},{"alias_kind":"arxiv_version","alias_value":"2109.13673v1","created_at":"2026-07-05T03:18:05.301228+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.13673","created_at":"2026-07-05T03:18:05.301228+00:00"},{"alias_kind":"pith_short_12","alias_value":"SDPKTVVE4JJD","created_at":"2026-07-05T03:18:05.301228+00:00"},{"alias_kind":"pith_short_16","alias_value":"SDPKTVVE4JJDDDAV","created_at":"2026-07-05T03:18:05.301228+00:00"},{"alias_kind":"pith_short_8","alias_value":"SDPKTVVE","created_at":"2026-07-05T03:18:05.301228+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/SDPKTVVE4JJDDDAV3DNAHUKL67","json":"https://pith.science/pith/SDPKTVVE4JJDDDAV3DNAHUKL67.json","graph_json":"https://pith.science/api/pith-number/SDPKTVVE4JJDDDAV3DNAHUKL67/graph.json","events_json":"https://pith.science/api/pith-number/SDPKTVVE4JJDDDAV3DNAHUKL67/events.json","paper":"https://pith.science/paper/SDPKTVVE"},"agent_actions":{"view_html":"https://pith.science/pith/SDPKTVVE4JJDDDAV3DNAHUKL67","download_json":"https://pith.science/pith/SDPKTVVE4JJDDDAV3DNAHUKL67.json","view_paper":"https://pith.science/paper/SDPKTVVE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2109.13673&json=true","fetch_graph":"https://pith.science/api/pith-number/SDPKTVVE4JJDDDAV3DNAHUKL67/graph.json","fetch_events":"https://pith.science/api/pith-number/SDPKTVVE4JJDDDAV3DNAHUKL67/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SDPKTVVE4JJDDDAV3DNAHUKL67/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SDPKTVVE4JJDDDAV3DNAHUKL67/action/storage_attestation","attest_author":"https://pith.science/pith/SDPKTVVE4JJDDDAV3DNAHUKL67/action/author_attestation","sign_citation":"https://pith.science/pith/SDPKTVVE4JJDDDAV3DNAHUKL67/action/citation_signature","submit_replication":"https://pith.science/pith/SDPKTVVE4JJDDDAV3DNAHUKL67/action/replication_record"}},"created_at":"2026-07-05T03:18:05.301228+00:00","updated_at":"2026-07-05T03:18:05.301228+00:00"}