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This paper presents a method for voice conversion using deep neural networks (DNNs) trained with multiple source speakers. The proposed DNNs can be used in two ways for different scenarios: 1) in the absence of training data for source speaker, the DNNs can be treated as source-speaker-independent models and perform conversions directly from arbitrary source speakers to certain target speaker; 2)...
In this paper, a new approach for function approximation is proposed to obtain better approximated performance. It is well known that gradient-based learning algorithms such as backpropagation (BP) algorithm have good ability of local search, whereas particle swarm optimization (PSO) has good ability of global search. Therefore, in the new approach, adaptive PSO (APSO) is applied to train network...
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