1 research outputs found
Our Practice Of Using Machine Learning To Recognize Species By Voice
As the technology is advancing, audio recognition in machine learning is
improved as well. Research in audio recognition has traditionally focused on
speech. Living creatures (especially the small ones) are part of the whole
ecosystem, monitoring as well as maintaining them are important tasks. Species
such as animals and birds are tending to change their activities as well as
their habitats due to the adverse effects on the environment or due to other
natural or man-made calamities. For those in far deserted areas, we will not
have any idea about their existence until we can continuously monitor them.
Continuous monitoring will take a lot of hard work and labor. If there is no
continuous monitoring, then there might be instances where endangered species
may encounter dangerous situations. The best way to monitor those species are
through audio recognition. Classifying sound can be a difficult task even for
humans. Powerful audio signals and their processing techniques make it possible
to detect audio of various species. There might be many ways wherein audio
recognition can be done. We can train machines either by pre-recorded audio
files or by recording them live and detecting them. The audio of species can be
detected by removing all the background noise and echoes. Smallest sound is
considered as a syllable. Extracting various syllables is the process we are
focusing on which is known as audio recognition in terms of Machine Learning
(ML).Comment: 16 page