vllm-omni/benchmarks/build_dataset/download_process_data_seedtts.md

Benchmark Dataset Preparation Guide

This guide describes how to download and prepare the SeedTTS test dataset for benchmarking Qwen-Omni models.

Prerequisites

• Python 3.8+
• gdown for downloading from Google Drive
• Access to the benchmark scripts

Steps

1. Navigate to the Dataset Directory

cd benchmarks/build_dataset

2. Install Dependencies

pip install gdown

3. Download the SeedTTS Test Dataset

Download the dataset from Google Drive:

gdown --id 1GlSjVfSHkW3-leKKBlfrjuuTGqQ_xaLP

4. Extract the Dataset

tar -xf seedtts_testset.tar

5. Prepare the Metadata File

Copy the English metadata file to the working directory:

cp seedtts_testset/en/meta.lst meta.lst

6. Extract Prompts

Extract the first N prompts from the metadata file:

# Extract top 100 prompts (adjust -n for different amounts)
python extract_tts_prompts.py -i meta.lst -o top100.txt -n 100

Options:

• -i, --input: Input metadata file (default: meta.lst)
• -o, --output: Output prompts file (default: prompts.txt)
• -n, --num-lines: Number of prompts to extract (required)

7. Clean Up (Optional)

Remove temporary files to save disk space:

rm -rf seedtts_testset
rm seedtts_testset.tar
rm meta.lst

Quick Start (All-in-One)

# Full setup and benchmark
cd benchmarks/build_dataset
pip install gdown
gdown --id 1GlSjVfSHkW3-leKKBlfrjuuTGqQ_xaLP
tar -xf seedtts_testset.tar
cp seedtts_testset/en/meta.lst meta.lst
python extract_tts_prompts.py -i meta.lst -o top100.txt -n 100
rm -rf seedtts_testset seedtts_testset.tar meta.lst