Inspiration

I chose this project because I enjoy birding and being in nature. I wanted to implement a classifier that would help improve my birding experiences, as well as keep track of the different species of birds that live near me.

How I built it

I used Sci-kit Learn's PCA method to keep the most important components of the spectrograms and passed them into Sci-kit's SVM method to classify the bird call.

Challenges I ran into

Converting the audio files to usable data was challenging and took a very long time. This left me with little time to try different hyperparameters for my model.

Accomplishments that we're proud of

I am proud of completing the web app and having it output a bird species based on the input bird call. As well as my model being a lot more accurate than random guessing.

What we learned

I learned how to successfully implement a machine learning model as well as make a functioning web app.

What's next for Bird Call Classifier

I plan on implementing a CNN to classify the bird calls to increase the accuracy as the accuracy of my current model isn't as high as I'd hoped for.

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