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Speaker clustering is the task of differentiating speakers in a recording. Ina way, the aim is to answer "who spoke when" in audio recordings. A commonmethod used in industry is feature extraction directly from the recordingthanks to MFCC features, and by using well-known techniques such as GaussianMixture Models (GMM) and Hidden Markov Models (HMM). In this paper, we studiedneural networks (especially CNN) followed by clustering and audio processing inthe quest to reach similar accuracy to state-of-the-art methods.

Speaker Clustering With Neural Networks And Audio Processing