Parselmouth for bioacoustics: automated acoustic analysis in Python-Reference-Cited by-同舟云学术

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Parselmouth for bioacoustics: automated acoustic analysis in Python

Published:2023-10-13 Issue: Volume: Page:1-17
ISSN:0952-4622
Container-title:Bioacoustics
language:en
Short-container-title:Bioacoustics

Author:

Jadoul Yannick¹²^ORCID,de Boer Bart²^ORCID,Ravignani Andrea¹³⁴^ORCID

Affiliation:

1. Comparative Bioacoustics Group, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands

2. Artificial Intelligence Lab, Vrije Universiteit Brussel, Elsene, Belgium

3. Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark

4. Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy

Funder

National Research Foundation

Publisher

Informa UK Limited

Subject

Ecology,Ecology, Evolution, Behavior and Systematics

Link

https://www.tandfonline.com/doi/pdf/10.1080/09524622.2023.2259327

Reference65 articles.

1. Sensorimotor adaptation of voice fundamental frequency in Parkinson's disease

2. Large-scale iterated singing experiments reveal oral transmission mechanisms underlying music evolution

3. Static and dynamic formant scaling conveys body size and aggression

4. warbleR: an r package to streamline analysis of animal acoustic signals

5. Beguš G Leban A Gero S. 2023. Encoding of speech in convolutional layers and the brain stem based on language experience. https://arxiv.org/abs/2303.10931.

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1. Training Harbor Seals to Participate in Vocal Learning Experiments in a Zoo;2024-08-27

2. Bioacoustic classification of a small dataset of mammalian vocalisations using deep learning;Bioacoustics;2024-07-02

3. thebeat: A Python package for working with rhythms and other temporal sequences;Behavior Research Methods;2024-02-02

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