Sentence examples for model for voice from inspiring English sources

Following that, the new MP3 Model for voice streams in the IP environment will be formulated.

The relatively low accuracy of the model for voice implies that it is difficult to find a stable diagnostic rule for voice.

In the diagnostic model for voice, the accuracy of the test set drastically decreased compared to that of the training set, which meant that the validity of the diagnostic model for voice was less than that of the other individual diagnostic models.

The individual diagnostic accuracies in the test set were slightly lower than those of the training set; however, the decrease in accuracy was within an acceptable range, except for the model for voice.

In addition, the coefficient of determination R for the model for voice was relatively lower than the others (see Additional files 15, 16, 17, 18, 19, 20, 21 and 22).

Such an observation does not fit well with current models for voice-identity processing, which by-and-large assume a common sequential analysis of the incoming voice signal, regardless of voice familiarity.

Group therapy has frequently been adopted as a service delivery model for providing voice therapy.

This traction has allowed Amazon to generate developer interest, despite the lack of a monetization model for their voice apps until more recently, with the introduction of paid subscriptions for Alexa skills.

A single, large DNN acoustic model for mobile voice search was trained with the original labels and soft targets from an ensemble of DNNs having different parameter initializations but the same size, input features, and training set, and WER was reduced from 10.9 to 10.7 % on a development set, matching the WER of the ensemble.

The MAP approach [29] considers a harmonic model for the voiced speech so that each windowed signal is expressed with a generalized linear model whose basic functions depend on the fundamental frequency and number of harmonic partials.

The extracted features described prosody and audio quality in combination with spectral and cepstral parameters to train Gaussian mixture models separately for voiced and unvoiced audio parts.