Biocoustic Sound Separation Based on FastICA and Infomax Algorithms

  • Norsalina Binti Hassan
  • Dzati Athiar RamliEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 547)


In bioacoustics technology, advances such as automated sound recognition based on animal vocalization help in biological research and environmental monitoring. However, in a noisy acoustic environment, where there will be interferences such as overlapping sounds made by multiple species, may greatly hamper the automated sound recognizer performance to identify the specific species. Hence, it is desirable to extract the sound made by the target species from the interferences as a pre-process prior to the recognition to get more accurate results. This paper exploits two Blind Source Separation (BSS) algorithms namely Info-max and FastICA to obtain the target frog sounds from the mixtures. The comparison of algorithm performances is expressed according to Signal-to-Interfere (SIR). The empirical simulation results show that FastICA outperforms Infomax in terms of separation quality.


Blind source separation (BSS) FastICA Infomax Frog sound 



This work was supported by Universiti Sains Malaysia under Research University (RU) Grant (No:1001.PELECT.8014057).


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Electrical and Electronic EngineeringUniversiti Sains Malaysia, Engineering CampusNibong TebalMalaysia

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