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In the Gaussian mixture model based online writer identification system, the writer specific models are usually learned by adapting the universal background model. However, among all the possible adapting plans, which one performs best is still an unsolved problem, as well as the underlying principles. Towards finding the answer, this paper analyses all the combinations of the parameter adaptation...
A deep learning approach has been proposed recently to derive speaker identifies (d-vector) by a deep neural network (DNN). This approach has been applied to text-dependent speaker recognition tasks and shows reasonable performance gains when combined with the conventional i-vector approach. Although promising, the existing d-vector implementation still can not compete with the i-vector baseline....
Music embedding often causes significant performance degradation in automatic speech recognition (ASR). This paper proposes a music-removal method based on denoising autoencoder (DAE) that learns and removes music from music-embedded speech signals. Particularly, we focus on convolutional denoising autoencoder (CDAE) that can learn local musical patterns by convolutional feature extraction. Our study...
In order to overcome the shortcomings brought by the narrow bandwidth of wireless network and limited computing ability of mobile terminals, this paper mainly proposes a 3D model transmission and interactive real-time rendering method over wireless local area network. Firstly, an optimized model simplified algorithm is presented for preserve the visually important vertices longer than other vertices...
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