Quickstart Model Setup

This repository publishes the benchmark dataset on Hugging Face, but the model artifacts used by the quickstart notebooks are separate. Some are gated, and a few require extra runtime packages or a local repo checkout.

The commands below make those dependencies explicit.

0. Environment Choice

The quickstarts and full benchmark runs should be launched from a model-specific environment. The public release includes the same environment specs that were maintained internally at /tealab-data/rjin02/AudioWatermarkBench/envs; use the checked-in copies under ../envs/ instead of relying on that absolute path.

For example:

cd envs
conda env create -f qwen3-tts.yml
conda activate qwen3
cd ..

See model_environments.md for the full model-to-environment map and notes on lock files or containers.

1. Common Login

Accept the gated model terms first, then log in once:

• Qwen3-TTS: https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-Base
• FishSpeech S1-mini: https://huggingface.co/fishaudio/s1-mini

huggingface-cli login

2. Qwen3-TTS Quickstart

Install the runtime package:

python -m pip install -U qwen-tts

Optional but recommended: pre-download the gated checkpoint into the repo so the notebook/script does not need live network access during generation.

huggingface-cli download Qwen/Qwen3-TTS-12Hz-1.7B-Base \
  --local-dir checkpoints/Qwen3-TTS-12Hz-1.7B-Base

Launch with the local checkpoint:

python scripts/run_qwen3tts_quickstart.py \
  --qwen-checkpoint-path checkpoints/Qwen3-TTS-12Hz-1.7B-Base

For the protection + Qwen3-TTS quickstart:

python scripts/run_protect_qwen3tts_quickstart.py \
  --qwen-checkpoint-path checkpoints/Qwen3-TTS-12Hz-1.7B-Base

3. FishSpeech Quickstart

Clone the inference repo and install it editable:

git clone https://github.com/fishaudio/fish-speech.git checkpoints/fish_speech
python -m pip install -e checkpoints/fish_speech

Download the gated S1-mini checkpoint into the location expected by the config:

huggingface-cli download fishaudio/s1-mini \
  --local-dir checkpoints/fish_speech/openaudio-s1-mini

Launch:

python scripts/run_fishspeech_quickstart.py \
  --fish-repo-dir checkpoints/fish_speech \
  --fish-ckpt-dir checkpoints/fish_speech/openaudio-s1-mini

4. Fish Audio S2 Quickstart

Fish Audio S2 (paper) ships from the same fishaudio/fish-speech repo as S1, so it reuses the fishspeech conda environment and code checkout above — make sure your checkout is up to date:

cd checkpoints/fish_speech && git pull && cd -
python -m pip install -e checkpoints/fish_speech

Download the S2-Pro checkpoint:

huggingface-cli download fishaudio/s2-pro \
  --local-dir checkpoints/fish_speech/s2-pro

Launch:

python scripts/run_fishspeech_s2_quickstart.py \
  --fish-repo-dir checkpoints/fish_speech \
  --fish-ckpt-dir checkpoints/fish_speech/s2-pro

5. SafeSpeech / BertVITS2 Setup

grnoise_on_libritts does not require the SafeSpeech surrogate checkpoints, but safespeech_on_libritts does.

The upstream helper in src/protection/safespeech/original_code/download_models.py downloads:

• OedoSoldier/Bert-VITS2-2.3 base model files: DUR_0.pth, D_0.pth, G_0.pth, WD_0.pth
• microsoft/deberta-v3-large
• microsoft/wavlm-base-plus
• speechbrain/spkrec-ecapa-voxceleb

Install the SafeSpeech dependency stack expected by the upstream code:

python -m pip install -r src/protection/safespeech/original_code/requirements.txt

Then download the surrogate assets:

python src/protection/safespeech/original_code/download_models.py

Launch the SafeSpeech variant:

python scripts/run_protect_qwen3tts_quickstart.py \
  --protect-config safespeech_on_libritts \
  --qwen-checkpoint-path checkpoints/Qwen3-TTS-12Hz-1.7B-Base

6. Public Dataset Only

All three quickstart scripts already support the public dataset release from Nanboy/RVCBench. They download only the dataset subset they need into data/, then point the benchmark at the local dataset root with dataset.use_hf_dataset=false.