[2603.19615] CAF-Score: Calibrating CLAP with LALMs for Reference-free Audio Captioning Evaluation

Computer Science > Sound arXiv:2603.19615 (cs) [Submitted on 20 Mar 2026] Title:CAF-Score: Calibrating CLAP with LALMs for Reference-free Audio Captioning Evaluation Authors:Insung Lee, Taeyoung Jeong, Haejun Yoo, Du-Seong Chang, Myoung-Wan Koo View a PDF of the paper titled CAF-Score: Calibrating CLAP with LALMs for Reference-free Audio Captioning Evaluation, by Insung Lee and 4 other authors View PDF HTML (experimental) Abstract:While Large Audio-Language Models (LALMs) have advanced audio captioning, robust evaluation remains difficult. Reference-based metrics are expensive and often fail to assess acoustic fidelity, while Contrastive Language-Audio Pretraining (CLAP)-based approaches frequently overlook syntactic errors and fine-grained details. We propose CAF-Score, a reference-free metric that calibrates CLAP's coarse-grained semantic alignment with the fine-grained comprehension and syntactic awareness of LALMs. By combining contrastive audio-text embeddings with LALM reasoning, CAF-Score effectively detects syntactic inconsistencies and subtle hallucinations. Experiments on the BRACE benchmark demonstrate that our approach achieves the highest correlation with human judgments, even outperforming reference-based baselines in challenging scenarios. These results highlight the efficacy of CAF-Score for reference-free audio captioning evaluation. Code and results are available at this https URL. Comments: Subjects: Sound (cs.SD); Artificial Intelligence (cs.AI); Comput...