Today I’m releasing Inflect v3: a family of local text-to-speech models: Mini, Micro, and Atom. Mini is the main model, with six voices and 34.31M parameters Mini provides vocal-event tags, reference voice-tuning, and 48 kHz enhancement. It runs on both CPU and CUDA. GitHub, installation, and examples: https://github.com/owenawsong/Inflect Try the playground: https://huggingface.co/spaces/owensong/Inflect-v3 Mini features reference-voice tuning: it allows one to make a profile from a recording and generate speech with it. This feature noticeably adjusts the voice toward your reference, though it won’t replicate every speaker accurately. Inflect Mini V3 also supports the following vocal-event tags: [laugh] · [sigh] · [gasp] · [cough] · [yawn] · [inhale] · [exhale] · [throat_clear] You can insert a tag whenever you want the sound to occur. Currently, the tags use repeatable performances: this causes repeated tags to result in limited variation. Tags also do not affect how the surrounding words are being spoken. The model family: Mini: 34.31M parameters. Quality-focused, with the features listed above. Micro: 11.79M parameters. A smaller neural speech model Atom: 157K parameters. An extremely tiny learned core Those numbers count the synthesis cores. The frontend and optional components add to the total. The weights and inference code are Apache 2.0. Third-party components keep their own licenses. Audio samples, benchmarks, and the settings used are on the model cards. Model collection: https://huggingface.co/collections/owensong/inflect-v3 If any sentence comes out wrong, send me the text, voice, and settings you used.   submitted by   /u/b111ue [link]   [comments]