Sentence examples for set of utterances from inspiring English sources

The set of utterances is pre-processed using the audio segmentation module presented in [86].

However, in the total variability space estimation, a given speaker's entire set of utterances is regarded as having been produced by different speakers.

We trained networks on clean data only, as well as on the full set of utterances in the multi-condition training set.

If we suppose that a given target language's entire set of utterances is regarded as having been produced by different languages, a common pool of hidden variables acts as basis factors and represents the utterances from different languages.

We estimate the language total variability space by using the dataset shown in Section 5, and we suppose that a given target language's entire set of utterances is regarded as having been belonging to different language.

In these experiments, the recognition rate of a set of utterances (words, syllables, or sentences) by a group of observers, is computed under at least two different conditions, namely, unimodal auditory and bimodal audio-visual conditions [33].

The weights wtc, wjc, wvc, wdvc are fine-tuned using an optimization method which involves a series of simple metrics that compare a synthesized utterance to a set of test utterances.

The original supervector can not describe short utterances precisely because of insufficient phoneme data, while the relative reconstructed SVM supervectors use the relationship between a short utterance and a large set of datum utterances, which is a richer representation.

In order to perform unbiased comparisons, we split the training data into a smaller training set of 2000 utterances and a hold-out set of 1233 utterances.

Linguists need theoretical constructs that capture regularities going beyond the set of actual utterances, and that allow them to predict the properties of novel utterances.

Our training set includes 50 parallel utterances obtained from each of the speaker pairs and a separate set of 25 utterances of each source speaker are used to evaluate the system.