{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:POQ4Y2S653SKWHYIVXTDYKE5UU","short_pith_number":"pith:POQ4Y2S6","schema_version":"1.0","canonical_sha256":"7ba1cc6a5eeee4ab1f08ade63c289da510a95e786b70bc2c6631c7b6187f4a9a","source":{"kind":"arxiv","id":"2206.13404","version":3},"attestation_state":"computed","paper":{"title":"Avocodo: Generative Adversarial Network for Artifact-free Vocoder","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.SD"],"primary_cat":"eess.AS","authors_text":"Hanbin Bae, Jae-Sung Bae, Jinhyeok Yang, Junmo Lee, Taejun Bak, Young-Sun Joo","submitted_at":"2022-06-27T15:54:41Z","abstract_excerpt":"Neural vocoders based on the generative adversarial neural network (GAN) have been widely used due to their fast inference speed and lightweight networks while generating high-quality speech waveforms. Since the perceptually important speech components are primarily concentrated in the low-frequency bands, most GAN-based vocoders perform multi-scale analysis that evaluates downsampled speech waveforms. This multi-scale analysis helps the generator improve speech intelligibility. However, in preliminary experiments, we discovered that the multi-scale analysis which focuses on the low-frequency "},"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":"2206.13404","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2022-06-27T15:54:41Z","cross_cats_sorted":["cs.AI","cs.SD"],"title_canon_sha256":"88e7ac2c96d17f76bd7b02a2d4717621c4cb5518fd1daae6ed8f5ff01089c7fb","abstract_canon_sha256":"3d9523671df63ba39440aa7782db48622de8a3ab78f0d5f65e8dfcd79616af0d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:29:53.367996Z","signature_b64":"76fT3iPlDDp5sC4W6/AhuTGU30KG7lgXiCh6klZAcUhIeTd74AL09KGtF9zQO84Wz0N8zpStQioy3L0AWzCGDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7ba1cc6a5eeee4ab1f08ade63c289da510a95e786b70bc2c6631c7b6187f4a9a","last_reissued_at":"2026-07-05T05:29:53.367575Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:29:53.367575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Avocodo: Generative Adversarial Network for Artifact-free Vocoder","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.SD"],"primary_cat":"eess.AS","authors_text":"Hanbin Bae, Jae-Sung Bae, Jinhyeok Yang, Junmo Lee, Taejun Bak, Young-Sun Joo","submitted_at":"2022-06-27T15:54:41Z","abstract_excerpt":"Neural vocoders based on the generative adversarial neural network (GAN) have been widely used due to their fast inference speed and lightweight networks while generating high-quality speech waveforms. Since the perceptually important speech components are primarily concentrated in the low-frequency bands, most GAN-based vocoders perform multi-scale analysis that evaluates downsampled speech waveforms. This multi-scale analysis helps the generator improve speech intelligibility. However, in preliminary experiments, we discovered that the multi-scale analysis which focuses on the low-frequency "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.13404","kind":"arxiv","version":3},"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/2206.13404/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":"2206.13404","created_at":"2026-07-05T05:29:53.367632+00:00"},{"alias_kind":"arxiv_version","alias_value":"2206.13404v3","created_at":"2026-07-05T05:29:53.367632+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.13404","created_at":"2026-07-05T05:29:53.367632+00:00"},{"alias_kind":"pith_short_12","alias_value":"POQ4Y2S653SK","created_at":"2026-07-05T05:29:53.367632+00:00"},{"alias_kind":"pith_short_16","alias_value":"POQ4Y2S653SKWHYI","created_at":"2026-07-05T05:29:53.367632+00:00"},{"alias_kind":"pith_short_8","alias_value":"POQ4Y2S6","created_at":"2026-07-05T05:29:53.367632+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/POQ4Y2S653SKWHYIVXTDYKE5UU","json":"https://pith.science/pith/POQ4Y2S653SKWHYIVXTDYKE5UU.json","graph_json":"https://pith.science/api/pith-number/POQ4Y2S653SKWHYIVXTDYKE5UU/graph.json","events_json":"https://pith.science/api/pith-number/POQ4Y2S653SKWHYIVXTDYKE5UU/events.json","paper":"https://pith.science/paper/POQ4Y2S6"},"agent_actions":{"view_html":"https://pith.science/pith/POQ4Y2S653SKWHYIVXTDYKE5UU","download_json":"https://pith.science/pith/POQ4Y2S653SKWHYIVXTDYKE5UU.json","view_paper":"https://pith.science/paper/POQ4Y2S6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2206.13404&json=true","fetch_graph":"https://pith.science/api/pith-number/POQ4Y2S653SKWHYIVXTDYKE5UU/graph.json","fetch_events":"https://pith.science/api/pith-number/POQ4Y2S653SKWHYIVXTDYKE5UU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/POQ4Y2S653SKWHYIVXTDYKE5UU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/POQ4Y2S653SKWHYIVXTDYKE5UU/action/storage_attestation","attest_author":"https://pith.science/pith/POQ4Y2S653SKWHYIVXTDYKE5UU/action/author_attestation","sign_citation":"https://pith.science/pith/POQ4Y2S653SKWHYIVXTDYKE5UU/action/citation_signature","submit_replication":"https://pith.science/pith/POQ4Y2S653SKWHYIVXTDYKE5UU/action/replication_record"}},"created_at":"2026-07-05T05:29:53.367632+00:00","updated_at":"2026-07-05T05:29:53.367632+00:00"}