Ensemble learning with speaker embeddings in multiple speech task stimuli for depression detection

HIGHLIGHTS

SUMMARY

    Speaker embeddings such as i-vectors, d-vectors, and x-vectors have shown their superiority in speaker recognition (Variani et_al, 2014; Wang et_al, 2017), and depression detection (EgasLópez et_al, 2022). The final results were then obtained using MLP based on the new features. emotion recognition (Vekkot et_al, 2019), Alzheimer`s disease (AD) detection (Egas López et_al, 2019), Parkinson`s disease (PD) detection (Garcia et_al, 2017), and depression detection (Cummins et_al, 2014; Rani, 2017; Afshan et_al, 2018; Mobram and Vali, 2022). X-vectors, the new state-of-the-art speaker embeddings, have been . . .

     

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