VTS
No phone app
5.9No. 22 of 28
in AI Sound Effect Generators
in AI Sound Effect Generators
- Recognised40% of the score32
- Phone app26% of the score0
- Documented20% of the score82
- Free plan14% of the score30
- Free plan
- No
- Runs on
- self-hosted
Summary
VTS is ranked #22 of 28 in AI sound effect generators on Samsung Mobile US Press. It runs on Self-hosted.
Compared on AI sound effect generators
- Free plan
- Yesgithub.com
- Text-to-sound
- Yesgithub.com
- Reference input
- Yesgithub.com
- Download formats
- wavgithub.com
- Commercial use
- uncleargithub.com
- API access
- Nogithub.com
Facts
- Purpose
- VTS generates sound effects from a short vocal or audio sketch combined with a text prompt.github.com · 4 Oct 2026
- How it works
- It uses voice conditioning derived from dynamic audio features alongside text conditioning from a prompt.github.com · 4 Oct 2026
- Intended users
- The checkpoint is intended for research and creative sound-effect generation from vocal sketches or short audio sketches plus text prompts.huggingface.co · 4 Oct 2026
- Local inference
- The repository provides an inference-only package with local model and runtime code.github.com · 4 Oct 2026
- Checkpoint
- The inference code uses the pretrained checkpoint named dynamic_v3_0415.ckpt, which is available from the linked Hugging Face model repository.github.com · 4 Oct 2026
- Generation
- Generated WAV files are written to a chosen output directory, and the default output duration follows the input audio duration unless a duration is specified.github.com · 4 Oct 2026
- Hardware
- The quick-start inference example specifies the CUDA device.github.com · 4 Oct 2026
- Limits
- The model is optimized for short sound-effect style clips, and output quality depends on the checkpoint, input audio, prompt text, and sampling settings.huggingface.co · 4 Oct 2026
- Training
- Training code and dataset manifests are not included in the inference package.github.com · 4 Oct 2026
- Integrations
- The inference code uses google/flan-t5-base as its text encoder and includes local vocoder code.github.com · 4 Oct 2026
- API availability
- The model is not packaged as a Hugging Face Inference API pipeline and is not deployed by an Inference Provider.huggingface.co · 4 Oct 2026
- License
- The project and model checkpoint are listed under the MIT License.github.com · 4 Oct 2026
- Support
- The repository says to contact the maker at [email protected] with questions.github.com · 4 Oct 2026
- Voice conditioning
- Voice conditioning uses dynamic features derived from spectral centroid, RMS, and chroma-index signals.github.com · 4 Oct 2026
- Text encoder
- The inference path encodes text prompts with google/flan-t5-base.github.com · 4 Oct 2026
- Output
- Generated audio files are written as WAV files to the chosen output directory.github.com · 4 Oct 2026
- Generation length
- Output duration defaults to the input audio duration, can be configured, and the checkpoint is tuned for short sound-effect clips.github.com · 4 Oct 2026
- Sampling
- Sampling uses a local ODE solver and typically runs 64 steps with CFG scale 3.0.github.com · 4 Oct 2026
- Deployment
- The repository provides an inference-only package with local model and runtime code; training code and datasets are excluded.github.com · 4 Oct 2026
- Hardware setup
- The documented local requirements pin PyTorch and torchaudio CUDA 12.4 builds, with instructions to install matching builds for other CUDA drivers.github.com · 4 Oct 2026
- Checkpoint access
- If the Hugging Face repository requires authentication, inference setup uses an HF_TOKEN environment variable.github.com · 4 Oct 2026
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Where it ranks on Samsung Mobile US Press
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Sources
- github.com/thxxx/VTS· checked 4 Oct 2026
- huggingface.co/Daniel777/VTS· checked 4 Oct 2026