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Two separate models were trained.
Acoustic models were trained using tr.
Only the data with which models were trained was resampled.
All of these models were trained on the MINC dataset.
The models were trained using the machine learning library LIBSVM.
Then for each cluster, ANN and ANFIS models were trained to predict GL and CC values.
Elastic net regularized logistic regression models were trained using a training set containing 1679 individuals.
Both CNN-based and DNN-only models were trained for 500 epochs.
For both evaluations, the acoustic models were trained using clean and/or multi-condition training datasets.
Two GMM models were trained, one for neutral speech the other for stressed speech.
The acoustic models were trained using the Spanish data from 2006 TC-STAR ASR evaluation campaign7.
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