机译:选择训练数据以改善声学模型的判别训练
Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei 116, Taiwan;
Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei 116, Taiwan;
Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei 116, Taiwan;
continuous speech recognition; discriminative training; acoustic models; data selection; phone accuracy; entropy;
机译:通过从多个ASR系统的假设中进行区分数据选择来半监督声学模型训练
机译:基于区分数据选择的自动演讲转录,用于轻度监督的声学模型训练
机译:从多个ASR系统假设中进行区分数据选择,以进行无监督的声学模型训练
机译:培养数据选择,以改善声学模型的鉴别培训
机译:用于语音识别的最佳生成和判别声学模型训练。
机译:通过语音分离和联合自适应训练提高深度神经网络声学模型的鲁棒性
机译:声学模型判别训练的训练数据选择