Measuring Sound Symbolism in Audio-visual Models
| Autor: | Tseng, Wei-Cheng, Shih, Yi-Jen, Harwath, David, Mooney, Raymond |
|---|---|
| Rok vydání: | 2024 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | Audio-visual pre-trained models have gained substantial attention recently and demonstrated superior performance on various audio-visual tasks. This study investigates whether pre-trained audio-visual models demonstrate non-arbitrary associations between sounds and visual representations$\unicode{x2013}$known as sound symbolism$\unicode{x2013}$which is also observed in humans. We developed a specialized dataset with synthesized images and audio samples and assessed these models using a non-parametric approach in a zero-shot setting. Our findings reveal a significant correlation between the models' outputs and established patterns of sound symbolism, particularly in models trained on speech data. These results suggest that such models can capture sound-meaning connections akin to human language processing, providing insights into both cognitive architectures and machine learning strategies. Comment: Errors in the introduction part that might potentially affect the integrity of the paper. Withdraw at the point. Will replace with an updated version in the future |
| Databáze: | arXiv |
| Externí odkaz: |
|