Sentence examples for set trained on from inspiring English sources

They say that training data with low SNR values reduces the speech discrimination of the trained HMM set, and it may be advantageous to employ an HMM set trained on data with higher SNR value.

Our results show that DNN-based models outperform HMMs and unit selection on both the realism and expressiveness of the generated talking heads, while in terms of adaptation we can successfully adapt an audio-visual HMM set trained on a neutral speaking style database to a target emotion.

Examples of sentences labeled as Intervention, Outcome Measure and Participants in Set 1. Results for four way classification on the manually annotated test set trained on the structured set, Set 2 are documented in Table 7.

More specifically, we note that the pathway features obtained using the GPF method involve not only the leading edge gene expressions for a given pathway p, but that these expressions are weighted by the gene weights w pi of these leading edge genes, inherited from the same training set when trained on the set of all genes.

This means that the single-Gaussian HMM set is trained on unwarped features and tested on warped features for different warps throughout the search space.

In order to use the two-view method for adding unlabeled instances to the training set, classifiers were trained on each set of features (i.e., one with review centric features and another with reviewer centric ones).

Generally a single-Gaussian HMM set which is trained on all available training data is used to estimate the warp factor.

In case of Feature Set I, classifier was trained on features calculated using the training set and predictions were made on subjects in test set.

Both sets of models were trained on the DMap expression data set of 38 distinct hematopoietic cell populations.

Hence, these labels annotate the training set, and the model has been specifically trained on this set.

In order to determine the optimal choice of uniform window length τ w for parsing the solo recordings, we performed three sets of recognition experiments based on a matched setting (train on solo, test on solo) and cross-domain setting (train on solo, test on RWC or train on RWC, test on solo).