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Victoire Djimna Noyum


Coop Masters, 2019/2021

While at Aims, Victoire worked on singer’s identification using Support vector machine (SVM) and Gaussian Mixture Model (GMM) as the machine learning models. Her work mainly consisted in implementing discrete wavelets transform (DWT) as a feature extraction technique on vocal signals and see if it better performs that Mel frequency cepstral coefficient (MFCC) which is the common technique used in audio signal.

Victoire currently works as data scientist Fellow at at on AI solutions for mental health. Prior to that, she received the Mathematical Science for Climate change Resilience (MS4CR) scholarship with ICRISAT (International crops research institute for the semi-arid tropics).

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