Articulino-DE-EN-Realtime-Stream-TTS Copyright 2026 eigenhand Licensed under the Apache License, Version 2.0 (see LICENSE). --------------------------------------------------------------------------- Training data --------------------------------------------------------------------------- The model was trained on the following corpora. The first three are licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/), which requires this attribution. Keep this NOTICE when you redistribute the model. - Emilia-YODAS, German subset. Haorui He et al., Amphion, "Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation" (2024); built on YODAS (Xinjian Li et al., ESPnet / WAVLab). CC BY 4.0. https://huggingface.co/datasets/amphion/Emilia-Dataset Only the YODAS part was used; the rest of Emilia (CC BY-NC 4.0) was not. - Hi-Fi TTS 2, selected English chapters. Ryan Langman et al., NVIDIA. CC BY 4.0. https://huggingface.co/datasets/nvidia/hifitts-2 - CML-TTS, German. Frederico S. Oliveira et al. CC BY 4.0. https://www.openslr.org/146/ Also used, without an attribution requirement: - Mozilla Common Voice 27.0, German. CC0 1.0. https://commonvoice.mozilla.org - Thorsten-Voice datasets, Thorsten Mueller. CC0 1.0. https://www.thorsten-voice.de - HUI-Audio-Corpus-German, iisys (Hof University). Audio from LibriVox (public domain). https://github.com/iisys-hof/HUI-Audio-Corpus-German No changes were made to the content of these corpora other than resampling to 24 kHz, cutting, filtering and text normalization for training. --------------------------------------------------------------------------- Design credit --------------------------------------------------------------------------- The overall recipe (letter-level text, duration predictor, flow-matching DiT on 25 Hz latents, 16-step teacher distilled with DMD2 into a 4-step student, separate latent decoder) follows the model card of EMA Lightning by Canberk Aslan (Apache License 2.0), https://huggingface.co/canberkkkkkk/ema-lightning. No code, weights, data or samples of EMA Lightning are included or were used.