Sentence examples for total variability space from inspiring English sources

We call language total variability space language-dependent total variability space when the total variability space is related to language-dependent GMM.

Then, the process of language total variability space estimation is exactly the same as the process of total variability space estimation and eigenvoice space estimation in speaker recognition.

In language total variability space estimation, total variability space is estimated relative to UBM, which is language, speaker, channel, gender, and environment independent.

After training the total variability space, we extracted i-vector and i-supervector for all utterances.

First, language total variability space and language-dependent total variability spaces are estimated.

Multiple total factor vector is extracted with similar method by using language-dependent GMM instead of language-independent UBM and using language-dependent total variability space instead of language total variability space as in Equation (4).

Then L language-dependent total variability spaces are estimated by using those language dependent GMMs instead of language-independent UBM.

Extended from traditional MAP adaptation approach to the i-vector adaptation approach, Gaussian components are no longer assumed to be independently distributed, total variability can be captured by a low-dimensional factor space, it means that sparse training data can give a global adaptation of total Gaussian components.

This sub-space captures the highest amount of total variability.

The total variability approach in speaker recognition relaxes the independent assumption between speaker and channel variability spaces in JFA speaker recognition [16].

The synthetic variables accounted for 46%to87%7% of the total variability.