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Data Set 1 :Male-Female(2 speakers) - GitHub Pages
https://bscharan.github.io/DSP320_project_website/#:~:text=The%20mean%20values%20of%20the%20MFCCs%20between%20the,speech%20audio%20of%20different%20speakers%20are%20obtained%20seperately.
K-Means Clustering and PCA to categorize music by …
https://towardsdatascience.com/k-means-clustering-and-pca-to-categorize-music-by-similar-audio-features-df09c93e8b64
With the help of sklearn, we can obtain the cluster labels for each track in just 3 lines of code. kmeans_pca = KMeans (n_clusters=n_clusters, …
Discovering Descriptive Music Genres Using K-Means …
https://medium.com/latinxinai/discovering-descriptive-music-genres-using-k-means-clustering-d19bdea5e443
Applying K-Means Clustering On All Tracks In short, K-Means Clustering is a technique that categorizes data based on the mean …
Audio signal feature extraction and clustering | by Aakash ...
https://medium.com/heuristics/audio-signal-feature-extraction-and-clustering-935319d2225
With that you have successfully understood and implemented you very own K-means audio signal clustering algorithm. If you wish to improve the …
Audio Clustering with Deep Learning | by Rida Khan | Medium
https://ridakhan5.medium.com/audio-clustering-with-deep-learning-a7991d605fa5
The output is the compressed version of the samples thereby extracting important features. I used these features to cluster the audio samples using K-Means algorithm into 20 possible clusters. Figure 1: Model Structure. 3.1 Dataset, Implementation Details & Spectrograms.
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