17 citations · 27 across the 11 of their papers we have counts for
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cs.SD2022★ 1 cited
AVES: Animal Vocalization Encoder based on Self-Supervision
Masato Hagiwara
The lack of annotated training data in bioacoustics hinders the use of large-scale neural network models trained in a supervised way. In order to leverage a large amount of unannot…
cs.SD2022★ 1 cited
BEANS: The Benchmark of Animal Sounds
Masato Hagiwara, Benjamin Hoffman, Jen-Yu Liu +3
The use of machine learning (ML) based techniques has become increasingly popular in the field of bioacoustics over the last years. Fundamental requirements for the successful appl…
cs.SD2022★ 1 cited
Modeling Animal Vocalizations through Synthesizers
Masato Hagiwara, Maddie Cusimano, Jen-Yu Liu
Modeling real-world sound is a fundamental problem in the creative use of machine learning and many other fields, including human speech processing and bioacoustics. Transformer-ba…