Yakun Hu

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In this paper, we address the speech-based gender identification problem. Mel-Frequency Cepstral Coefficients (MFCC) of voice samples are typically used as the features for gender identification. However, MFCC-based classification incurs high complexity. This paper proposes a novel pitch-based gender identification system with a two-stage classifier to(More)
—In this paper, we address the problem of large population speaker identification under noisy conditions. Major techniques for speaker identification is based on Mel-Frequency Cepstral Coefficients (MFCC), Gaussian Mixture Model (GMM) and Universal Background Model (UBM) which we call MFCC+GMM and MFCC+GMM+UBM. The approaches are known to perform very well(More)
Genome-wide association studies (GWAS) on sporadic Parkinson’s disease (sPD) are mainly conducted in European and American populations at present, and the Han populations of Chinese mainland (HPCM) almost have not been studied yet. Here, we conducted a pooling GWAS combining a pathway analysis with 862,198 autosomal single nucleotide polymorphisms of(More)
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