标题： TTA-Bench：评估文本到音频模型的全面基准 显示英文标题

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

摘要： 文本到音频（TTA）生成已经取得了快速进展，但当前的评估方法仍然有限，主要关注感知质量，而忽视了鲁棒性、泛化能力和伦理问题。 我们提出了TTA-Bench，一个全面的基准，用于评估TTA模型在功能性能、可靠性和社会责任方面的表现。 它涵盖了七个维度，包括准确性、鲁棒性、公平性和毒性，并包括通过自动化和手动方法生成的2,999个多样化提示。 我们引入了一个统一的评估协议，结合了客观指标和来自专家和普通用户的超过118,000条人工标注。 十种最先进的模型在此框架下进行了基准测试，提供了对其优势和局限性的详细见解。 TTA-Bench为TTA系统的全面和负责任的评估设定了新标准。 数据集和评估工具在https://nku-hlt.github.io/tta-bench/上开源。 显示英文摘要

摘要： 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/.