Audio Retrieval with Natural Language Queries
Andreea-Maria Oncescu, A. Sophia Koepke, Joao F. Henriques, Zeynep Akata, Samuel Albanie
INTERSPEECH
2021

Abstract
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.
(c) 2021 Explainable Machine Learning Tübingen Impressum