Higgs Audio v3: local TTS setup with Streamlit

This tutorial builds a local AI storyteller around Higgs Audio v3, with a Python and Streamlit dashboard that sends text to a TTS server on localhost. The presenter uses Google Antigravity as the coding environment and points viewers to project code, a requirements.txt file and model download commands in the linked repository.

The walkthrough uses a 4-bit quantized model to reduce download size and memory use. Downloading the model and starting the TTS server are prerequisites for the dashboard; the interface launches with streamlit run app.py. The presenter gives conflicting model sizes, first 5 billion parameters and later 4 billion, and provides no specific hardware requirements to support the claim that it runs on any PC.

Story templates include fantasy adventure, suspense thriller and a children's fairy tale. Users can edit the text and add tags for emotion, whispering or sound effects. The presenter recommends pairing a laughter tag with a written vocalization such as "haha". The dashboard plays generated audio and offers a WAV download. Its timeout message suggests shorter text or fewer tokens.

The presenter reports generation in 5 to 6 seconds for the example and claims support for 102 languages, with 85 at production quality. These are speaker claims rather than independently verified results. The demo also includes a note describing its use as non-commercial.