An Architecture for Animal Sound Identification based on Multiple Feature Extraction and Classification Algorithms
Keyword(s):
Automatic identification of animals is extremely useful for scientists, providing ways to monitor species and changes in ecological communities. The choice of effective audio features and classification techniques is a challenge on any audio recognition system, especially in bioacoustics that commonly uses several algorithms. This paper presents a novel software architecture that supports multiple feature extraction and classification algorithms to help on the identification of animal species from their recorded sounds. This architecture was implemented by the WASIS software, freely available on the Web.
2019 ◽
Vol 8
(10)
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pp. 2443-2445
Evaluation of Iris Recognition System on Multiple Feature Extraction Algorithms and its Combinations
2015 ◽
Vol 4
(8)
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pp. 592-598
2013 ◽
Vol 760-762
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pp. 1501-1504
2018 ◽
Vol 6
(6)
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pp. 307
2018 ◽
2019 ◽
Vol 12
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