The Sound of Absence: Audio-Language Embedding Models Struggle with Negation
Audio-language embedding models such as CLAP are widely evaluated on matching present sound events, but rarely on negation. We show this affirmation-only evaluation hides a key limitation: these models fail to encode negated sound concepts, mapping affirmative and negated captions to nearly identical representations. To expose this blind spot, we introduce NegEval-Audio, a framework that converts existing datasets into two negation-aware tasks, Retrieval-Neg and Multiple-Choice Negation (MCQ-Neg), to probe whether models distinguish present from absent events. On AudioCaps and Clotho, performance degrades sharply under negation, with negation-type MCQ accuracy falling far below chance, an...
| Authors | Chun-Yi Kuan, Hung-yi Lee |
|---|---|
| Primary category | eess.AS |
| Published | 14 July 2026 |
| Last updated at source | 14 July 2026 |
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