# TTA-Bench: A Comprehensive Benchmark for Evaluating Text-to-Audio Models

arXiv: https://arxiv.org/abs/2509.02398 · HTML: https://mlsanity.com/paper/2509.02398/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Sep 2025.

## Built on by (most cited first, 7 of 7)

- [AVGen-Bench: A Task-Driven Benchmark for Multi-Granular Evaluation of Text-to-Audio-Video Generation](https://mlsanity.com/paper/2604.08540/) (2026)
- [AQAScore: Evaluating Semantic Alignment in Text-to-Audio Generation via Audio Question Answering](https://mlsanity.com/paper/2601.14728/) (2026)
- [MoEScore: Mixture-of-Experts-Based Text-Audio Relevance Score Prediction for Text-to-Audio System Evaluation](https://mlsanity.com/paper/2601.06829/) (2026)
- [A Production-Oriented Framework for Evaluation of SFX Generation](https://mlsanity.com/paper/2607.09973/) (2026)
- [AudioScape-TTA: A Structured Soundscape Benchmark for Fine-Grained Text-to-Audio Evaluation](https://mlsanity.com/paper/2608.04479/) (2026)
- [TurboT2VA: Fast Large-Scale Text-to-Video-Audio Generation via Score-Regularized Consistency Distillation](https://mlsanity.com/paper/2608.24674/) (2026)
- [AV-SafetyBench: A Safety Benchmark for Text-to-Audio-Video Generation](https://mlsanity.com/paper/2609.06991/) (2026)

## Abstract (arXiv)

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 and responsible evaluation of TTA systems. The dataset and evaluation tools are open-sourced at https://nku-hlt.github.io/tta-bench/.