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Automatic emotion recognition from speech has received an increasing amount of interest in recent years, and many speech emotion recognition methods have been presented, in which the training and testing procedures are often conducted on the same corpus. However, in practice, the training and testing speech utterances are collected from different conditions or devices, which will have adverse effects...
In practical situations, the emotional speech utterances are often collected from different devices and conditions, which will obviously affect the recognition performance. To address this issue, in this paper, a novel transfer non-negative matrix factorization (TNMF) method is presented for cross-corpus speech emotion recognition. First, the NMF algorithm is adopted to learn a latent common feature...
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