Exact(4)
Since DNNs are powerful in transforming features through many layers of nonlinear transformations, it is common to splice the input features with a long context window to learn the temporal dynamic information automatically.
Speech feature vectors are obtained by transforming features linearly using a time-invariant transform matrix generated by our method.
Based on the manifold assumption of continuously transforming features, an unsupervised learning algorithm is also presented to learn the features used by the classifier.
Feature selection/reduction techniques usually are not effective in this case because of the overfitting problem as well as the problem of lack of interpretation while transforming features.
Similar(56)
Once again it's not a massive reality transforming feature but it does make a real difference.
However, these technologies all rely on feature transformations which transform features from original state to a form which can be distinguished from other data, subsequently generating cryptographic keys based on the transformation of the features.
In the training stage, DAE and BF-DNN models for feature transformation and speaker models with transformed features are trained.
Two of the most common second-order features are Fourier transform features and co-occurrence features.
The resulting transformed features for these random variables are then used as modified shape descriptors.
Then, the transformed features and speaker models are used to calculate the likelihood of each speaker.
In this nonlinear case, the mean of transformed features is not generally the same as the transformed mean value.
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