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As the technology is advancing, audio recognition in machine learning isimproved as well. Research in audio recognition has traditionally focused onspeech. Living creatures (especially the small ones) are part of the wholeecosystem, monitoring as well as maintaining them are important tasks. Speciessuch as animals and birds are tending to change their activities as well astheir habitats due to the adverse effects on the environment or due to othernatural or man-made calamities. For those in far deserted areas, we will nothave 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 nocontinuous monitoring, then there might be instances where endangered speciesmay encounter dangerous situations. The best way to monitor those species arethrough audio recognition. Classifying sound can be a difficult task even forhumans. Powerful audio signals and their processing techniques make it possibleto detect audio of various species. There might be many ways wherein audiorecognition can be done. We can train machines either by pre-recorded audiofiles or by recording them live and detecting them. The audio of species can bedetected by removing all the background noise and echoes. Smallest sound isconsidered as a syllable. Extracting various syllables is the process we arefocusing on which is known as audio recognition in terms of Machine Learning(ML).

Our Practice Of Using Machine Learning To Recognize Species By Voice