TTA-Bench: A Comprehensive Benchmark for Evaluating Text-to-Audio Models
Hui Wang, Cheng Liu, Junyang Chen, Haoze Liu, Yuhang Jia, Shiwan Zhao, Jiaming Zhou, Haoqin Sun, Hui Bu, Yong Qin
Abstract
Text-to-Audio (TTA) generation has made rapid progress, but current evaluation methods remain narrow, focusing mainly on perceptual quality while overlooking robustness, generalization, and ethical concerns. We present TTA-Bench, a comprehensive benchmark for evaluating TTA models across functional performance, reliability, and social responsibility. It covers seven dimensions including accuracy, robustness, fairness, and toxicity, and includes 2,999 diverse prompts generated through automated and manual methods. We introduce a unified evaluation protocol that combines objective metrics with over 118,000 human annotations from both experts and general users. Ten state-of-the-art models are benchmarked under this framework, offering detailed insights into their strengths and limitations. TTA-Bench establishes a new standard for holistic evaluation of TTA systems.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers1
Ask how each one uses itBuilds on10
- Zero-Shot Text-to-Image GenerationAditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray et al.ICML 2021 · 6,356 citations
- AudioLDM: Text-to-Audio Generation with Latent Diffusion ModelsHaohe Liu, Zehua Chen, Yi Yuan, Xinhao Mei et al.ICML 2023 · 773 citations
- Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion ModelsRongjie Huang, Jiawei Huang, Dongchao Yang, Yi Ren et al.ICML 2023 · 469 citations
- HRS-Bench: Holistic, Reliable and Scalable Benchmark for Text-to-Image ModelsEslam Mohamed Bakr, Pengzhan Sun, Xiaoqian Shen, Faizan Farooq Khan et al.ICCV 2023 · 115 citations
- Masked Audio Generation using a Single Non-Autoregressive TransformerAlon Ziv, Itai Gat, Gaël Le Lan, Tal Remez et al.ICLR 2024 · 69 citations
Related papers
- T2AV-Compass: Towards Unified Evaluation for Text-to-Audio-Video GenerationZhe Cao, Tao Wang, Jiaming Wang, Yanghai Wang et al.ICML 2026 · 13 citations
- VABench: A Comprehensive Benchmark for Audio-Video GenerationDaili Hua, Xizhi Wang, Bohan Zeng, Xinyi Huang et al.CVPR 2026 · 25 citations
- AudioTrust: Benchmarking The Multifaceted Trustworthiness of Audio Large Language ModelsKai Li, Can Shen, Yile Liu, Jirui Han et al.ICLR 2026 · 17 citations
- VBench: Comprehensive Benchmark Suite for Video Generative ModelsZiqi Huang, Yinan He, Jiashuo Yu, Fan Zhang et al.CVPR 2024
- AIR-Bench: Benchmarking Large Audio-Language Models via Generative ComprehensionQian Yang, Jin Xu, Wenrui Liu, Yunfei Chu et al.ACL 2024
