Classifying sound using Machine Learning (Artificial Summit February 2020 @ KnowIt)

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Wow, how am I just coming across this lol. Super helpful addition to your other one I saw. Thanks, Jon. Around 48:50 you're talking about labeling for multiple sounds so I just want to clarify. Let's say I want to detect birds. But it's in an area with a lot of wolves who howl a lot. Let's also assume that those are the only two things making noise at all times, wolves and birds. When I classify the dataset to train my model on...before watching this video, I would have originally thought, I should make two classes, "Birds" and "No Birds". But if there are a lot of wolves howling, would I improve my detection if I have "Birds", "No Birds", and "Birds and Wolves." In other words, is adding a third class where there is kind of a mixed sound between the one I want and the interfering audio going to improve my ability to know when birds are chirping around?

peterm.

hey there! thanks for the amazing talk.
i am still confused about labelling training data for the model.

in my scenario, i have to detect the whistle sound generated by referee during a live sports event. how do i approach training my dataset. i have audio clips from sample match which last over an hour. so if i use the clip to label whistle sounds from it, will it also not take into account the other sounds at the exact moment? suppose referee blows whistle at 2:00-2:10. if i label it as a whistle sound, will it also not include the noise coming from the crowd? how do i approach this problem?

ChintanShah-zw

Can you help me with my project about machine learning?

alaabarakat

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