3 accepted papers
The models based on convolutional neural network (CNN) have shown remarkable performance in spoofing detection for automatic speaker verification. In order to input data into CNN-based models in mini-batch unit, the shape of all data in each mini-batch must be equal. Therefore, the method to make al…
We propose a method to improve speaker verification performance when a test utterance is very short. In some situations with short test utterances, performance of ivector/probabilistic linear discriminant analysis systems degrades. The proposed method transforms short-utterance feature vectors to ad…
Few studies on speaker verification have directly used a deep neural network (DNN) as a classifier. It is difficult to directly apply a DNN as a discriminative model to speaker-verification tasks because the training data for each speaker are very limited. Therefore, a b-vector has been proposed to…