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Audio Retrieval with Natural Language Queries (2105.02192v2)

Published 5 May 2021 in cs.IR, cs.SD, and eess.AS

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.

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Authors (5)
  1. Andreea-Maria Oncescu (5 papers)
  2. A. Sophia Koepke (22 papers)
  3. João F. Henriques (55 papers)
  4. Zeynep Akata (144 papers)
  5. Samuel Albanie (81 papers)
Citations (75)

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