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Modeling time series data of varying length is important in different domains. There are two paradigms for modeling the varying length sequential data. Tasks such as speech recognition need modeling the temporal dynamics and the correlations among the features. Hidden Markov models (HMM) are used for these tasks. In tasks such as speaker recognition, audio classification and speech emotion recognition,...
Speaker independent emotion recognition is particularly difficult for the individual differences of acoustic character and culture background. So, relative features obtained by calculating the features change of emotion speech relative to natural speech are adopted to weaken the influence from the individual differences in the paper. Moreover, an improved ranked voting fusion system is proposed to...
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