{"paper":{"title":"Frequency domain variants of velvet noise and their application to speech processing and synthesis: with appendices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS","eess.SP"],"primary_cat":"cs.SD","authors_text":"Hideki Banno, Hideki Kawahara, Ken-Ichi Sakakibara, Masanori Morise, Tomoki Toda, Toshio Irino","submitted_at":"2018-06-18T16:35:47Z","abstract_excerpt":"We propose a new excitation source signal for VOCODERs and an all-pass impulse response for post-processing of synthetic sounds and pre-processing of natural sounds for data-augmentation. The proposed signals are variants of velvet noise, which is a sparse discrete signal consisting of a few non-zero (1 or -1) elements and sounds smoother than Gaussian white noise. One of the proposed variants, FVN (Frequency domain Velvet Noise) applies the procedure to generate a velvet noise on the cyclic frequency domain of DFT (Discrete Fourier Transform). Then, by smoothing the generated signal to design"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.06812","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"}