{"paper":{"title":"BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","eess.AS"],"primary_cat":"cs.LG","authors_text":"Adam Michalski, Alexis Moinet, \\'Alvaro Mart\\'in-Cortinas, Ammar Abbas, Arent van Korlaar, Arnaud Joly, Bartosz Putrycz, Elena Sokolova, Ewa Muszy\\'nska, Fan Yang, Fatih Beyhan, Guillermo C\\'ambara, Haohan Guo, Kayeon Yoo, Mateusz {\\L}ajszczak, Soledad L\\'opez Gambino, Sri Karlapati, Thomas Drugman, Yang Li","submitted_at":"2024-02-12T22:21:30Z","abstract_excerpt":"We introduce a text-to-speech (TTS) model called BASE TTS, which stands for $\\textbf{B}$ig $\\textbf{A}$daptive $\\textbf{S}$treamable TTS with $\\textbf{E}$mergent abilities. BASE TTS is the largest TTS model to-date, trained on 100K hours of public domain speech data, achieving a new state-of-the-art in speech naturalness. It deploys a 1-billion-parameter autoregressive Transformer that converts raw texts into discrete codes (\"speechcodes\") followed by a convolution-based decoder which converts these speechcodes into waveforms in an incremental, streamable manner. Further, our speechcodes are b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.08093","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2402.08093/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"}