A method for speaker normalization in deep neural network (DNN) based discriminative feature estimation for automatic speech recognition (ASR) is presented.
A method for speaker normalization in deep neural network (DNN) based discriminative feature estimation for automatic speech recog- nition (ASR) is ...
An approach is presented in this paper where spectrum based DNN inputs are augmented with speaker inputs that are derived from separate regression based ...
we can easily apply speaker normalization to this feature. Page 3. However, when training a neural network, the length of the feature is different, and the ...
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In training phase, the network is trained to distinguish between different speaker identities for creating the back- ground model. One of the crucial parts is ...
May 19, 2017 · Bibliographic details on Deep neural network trained with speaker representation for speaker normalization.
We investigate the concept of speaker adaptive training (SAT) in the context of deep neural network (DNN) acoustic models.
Speaker identification and speaker verification are the main tasks in the field of speaker recognition. The former involves inferring the speaker of.
At the training stage, speaker embeddings are learned in a speaker classification task. After that, the classification layers are removed, and the learned.
Jul 15, 2023 · We present a late fusion DNN model with RWs and GTCCs for speaker identification. We analyze the characteristics of RW and spectrum-based features.