Audio Retrieval with Natural Language Queries
About
We consider the task of retrieving audio using free-form natural language queries. To study this problem, which has received limited attention in the existing literature, we introduce challenging new benchmarks for text-based audio retrieval using text annotations sourced from the Audiocaps and Clotho datasets. We then employ these benchmarks to establish baselines for cross-modal audio retrieval, where we demonstrate the benefits of pre-training on diverse audio tasks. We hope that our benchmarks will inspire further research into cross-modal text-based audio retrieval with free-form text queries.
Andreea-Maria Oncescu, A. Sophia Koepke, Jo\~ao F. Henriques, Zeynep Akata, Samuel Albanie• 2021
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Audio Retrieval | AudioCaps | R@139.6 | 42 | |
| Cross-modal retrieval | Clotho (test) | R@19.6 | 29 | |
| Cross-modal retrieval | AudioCaps (test) | R@128.1 | 23 | |
| Audio Retrieval | Clotho | R@112.6 | 20 | |
| Text-to-Audio Retrieval | Clotho V1 | R@19.6 | 15 |
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