Text-to-Audio
LTX.io
English
ltx-audio
audio
audio-generation
speech
reference-conditioning
multi-speaker
flow-matching
diffusion
Instructions to use ngoctham/scena with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use ngoctham/scena with LTX.io:
# Install the LTX-2 pipelines git clone https://github.com/Lightricks/LTX-2.git cd LTX-2 uv sync --frozen
# Download the weights from this repo, plus the Gemma text encoder hf download ngoctham/scena --local-dir models/scena hf download google/gemma-3-12b-it-qat-q4_0-unquantized --local-dir models/gemma-3-12b
# Fast pipeline (distilled model, no distilled LoRA needed) uv run python -m ltx_pipelines.distilled \ --distilled-checkpoint-path models/scena/<distilled-checkpoint>.safetensors \ --spatial-upsampler-path models/scena/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8# HQ pipeline (two-stage, higher quality) uv run python -m ltx_pipelines.ti2vid_two_stages_hq \ --checkpoint-path models/scena/<checkpoint>.safetensors \ --distilled-lora models/scena/<distilled-lora>.safetensors 0.8 \ --spatial-upsampler-path models/scena/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8 - Notebooks
- Google Colab
- Kaggle
| license: other | |
| license_name: ltx-2-community-license | |
| license_link: https://huggingface.co/Lightricks/LTX-2/blob/main/LICENSE | |
| language: | |
| - en | |
| tags: | |
| - audio | |
| - text-to-audio | |
| - audio-generation | |
| - speech | |
| - reference-conditioning | |
| - multi-speaker | |
| - flow-matching | |
| - diffusion | |
| - ltx | |
| library_name: ltx-audio | |
| pipeline_tag: text-to-audio | |
| # ScenA β Reference-Driven Multi-Speaker Audio Scene Generation | |
| **ScenA** generates multi-speaker audio *scenes* (dialogue, conversation) from a text | |
| prompt, conditioned on one or more **reference-audio** clips that set the speakers' | |
| voices. It is an audio-only, reference-conditioned text-to-audio flow-matching DiT | |
| built on the LTX-2 architecture (~4B parameters, 48 layers). | |
| - π **Paper:** [arXiv:2606.19325](https://arxiv.org/abs/2606.19325) | |
| - π **Project page:** https://finmickey.github.io/scena/ | |
| - π» **Code:** https://github.com/finmickey/scena | |
| - π’ Lightricks Β· Tel Aviv University | |
| ## Files | |
| | file | size | contents | | |
| |---|---|---| | |
| | `scena.safetensors` | ~8.2 GB | the ScenA transformer + Gemma text-projection weights | | |
| | `audio_vae.safetensors` | ~365 MB | the audio VAE (encoder+decoder) + vocoder (bundled so you don't need the full LTX-2 model) | | |
| You also need the **Gemma-3-12B-IT** text encoder (`google/gemma-3-12b-it`, gated on HF). | |
| ## Quickstart | |
| ```bash | |
| git clone https://github.com/finmickey/scena | |
| cd scena | |
| pip install -e . # or: uv sync | |
| # download the checkpoint + audio VAE bundle | |
| huggingface-cli download mifinkelson/scena scena.safetensors audio_vae.safetensors --local-dir ./checkpoints | |
| ``` | |
| Two example reference voices ship with the repo under `examples/references/` β the same two voices | |
| drive both examples below, so this runs out of the box: | |
| ```python | |
| from ltx_pipelines.t2aud_ref_cond import T2AudRefCondPipeline | |
| pipe = T2AudRefCondPipeline( | |
| checkpoint_path="checkpoints/scena.safetensors", | |
| audio_vae_path="checkpoints/audio_vae.safetensors", | |
| gemma_root="/path/to/google/gemma-3-12b-it", | |
| ) | |
| refs = ["examples/references/reference_1.wav", "examples/references/reference_2.wav"] | |
| # A simple two-speaker dialogue | |
| pipe( | |
| prompt='The speaker from reference 1 says: "The taxi drivers are on strike again." The speaker from reference 2 says: "What for?" The speaker from reference 1 says: "They want the government to reduce the price of the gasoline." The speaker from reference 2 says: "It is really a hot potato."', | |
| ref_audio_paths=refs, | |
| duration=7.0, | |
| seed=1, | |
| ).save("dialogue.wav") | |
| # Farm at sunrise β the same two voices in a scene with sound effects | |
| pipe( | |
| prompt='A farm at sunrise: a rooster crows. Chickens cluck softly throughout. The speaker from reference 1 says with a yawn: "Way too early for this." The speaker from reference 2 chuckles: "Welcome to country life." The rooster crows again.', | |
| ref_audio_paths=refs, | |
| duration=8.0, | |
| seed=1, | |
| ).save("farm.wav") | |
| ``` | |
| ### Prompting guide | |
| - Refer to speakers as **"the speaker from reference 1"**, **"reference 2"**, β¦ matching the | |
| order of `ref_audio_paths`. | |
| - Put the spoken words **in quotes**; describe sound effects / ambience in plain prose | |
| (e.g. *"rain drums steadily on a tin roof"*, *"a roaring stadium crowd cheers"*). | |
| - Reference clips: clean single-speaker speech, up to ~20 s each β the more the better (any sample rate; mono or stereo). | |
| - You don't have to follow a strict turn-taking pattern; see the [demo page](https://finmickey.github.io/scena/) for more varied examples. | |
| - 60 inference steps, guidance ~7, and output durations up to ~20 s work best (the model was trained on β€20 s scenes). | |
| ## Citation | |
| ```bibtex | |
| @article{finkelson2026scena, | |
| title = {Reference-Driven Multi-Speaker Audio Scene Generation from In-the-Wild Priors}, | |
| author = {Finkelson, Michael and Segal, Daniel and Richardson, Eitan and Armon, Shahar and Goldring, Nani and Panet, Poriya and Zabari, Nir and Brazowski, Benjamin and Patashnik, Or and HaCohen, Yoav}, | |
| journal = {arXiv preprint arXiv:2606.19325}, | |
| year = {2026} | |
| } | |
| ``` | |
| ## License | |
| Released under the [LTX-2 Community License](https://huggingface.co/Lightricks/LTX-2/blob/main/LICENSE). | |