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  • 1Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, The Netherlands.

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Summary

Deep learning is revolutionizing computational bioacoustics for studying animal sounds and ecosystems. This review clarifies concepts, identifies knowledge gaps, and proposes a roadmap for future AI-driven ecological research.

Keywords:
AcousticsAnimal vocal behaviourBioacousticsDeep learningMachine learningPassive acoustic monitoringSound

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Area of Science:

  • Bioacoustics and Ecoacoustics
  • Computational Bioacoustics
  • Artificial Intelligence in Ecology

Background:

  • Animal vocalizations and soundscapes offer crucial insights into animal behavior, populations, and ecosystems.
  • The field of computational bioacoustics has rapidly advanced due to digital recording technology and progress in informatics, including big data, signal processing, and machine learning.
  • While deep learning methods are adapted from speech and image processing, unique challenges in bioacoustics data and tasks remain.

Approach:

  • This paper reviews the current state-of-the-art in deep learning applications for computational bioacoustics.
  • It clarifies key concepts and critically analyzes existing knowledge gaps within the field.
  • A principled roadmap is proposed to guide future research directions.

Key Points:

  • Deep learning methods, while powerful, require adaptation for the distinct characteristics of bioacoustic data.
  • Significant opportunities exist for applying AI to unlock previously unrealized ecological insights from audio data.
  • Addressing specific challenges in computational bioacoustics is essential for advancing ecological understanding.

Conclusions:

  • The integration of deep learning presents a transformative opportunity for bioacoustics and ecoacoustics.
  • Further research is needed to bridge the gap between AI advancements and ecological applications.
  • A community-driven roadmap can accelerate the use of AI in analyzing animal sounds for zoological and ecological discovery.