Sentence examples for model adaptation methods from inspiring English sources

In addition to speech enhancement and feature robustness techniques, MLLR [33], MAP [34] and PC-PMC model adaptation methods can be applied optionally on acoustic models to adapt the acoustic model parameters to speaker variations and environmental noises.

In this section, the proposed model interpolation method is compared to the model adaptation method.

We proposed a new environmental model adaptation method for robust speech recognition.

We propose a two-step model adaptation method consisting of feature normalization and semi-supervised learning adaptation.

We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments.

Some examples of the model adaptation method include the (constrained) maximum likelihood linear regression (CMLLR/MLLR) [30], maximum a posteriori (MAP) [37], and vector Taylor series (VTS) [38 40] based adaptation methods.

A well-known environmental model adaptation method is the parallel model combination technique [7], which combines both clean speech and noise models in the spectral domain to obtain noisy speech models.

We have shown that by using a model adaptation method in the training phase, the average EER of the LLR system was reduced to 6.5%, a relative reduction of 27% compared with our SVM systems.

The proposed model adaptation method yielded system accuracies up to 80.7% compared to 85.2% obtained for a system trained on the material recorded in the unseen acoustic setting itself.

The article "Quality of Service (QoS) Regulation in Secure Body Area Networks: System Modeling and Adaptation Methods" by Fr.

Model-transferring domain adaptation methods use a previously trained source classifier for adaptation purposes on a target domain.