Sentence examples for self normalization from inspiring English sources

After determining the self normalization warps by using the model space search approach summarized above, the rest of the normalization is similar to the offline VTLN.

In the on-the-fly experimentation, however, the warp is adjusted as more and more data becomes available from the same speaker, and normalized models and features are used to update the self-normalization warp, hence the alignments supplied by the recognizer are more accurate, yielding better estimates for the self-normalization warp.

We give the block-diagram for the application of this self-normalization front end (BISN w/MS-BTS) in Figure 4. Figure 4 The block diagram of the self normalizing front end (PMVDR w/BISN) in a real-word application scenario.

The averaged self-normalization warp tracks the fixed self-normalization warp, permitting slow variations within the same speaker.

Figure 5 The variation of the instantaneous self-normalization warp, averaged self-normalization warp, and fixed self-normalization warp (obtained from offline BISN w/MS-BTS), the speaker turns are also marked with a dashed line (the averaged self-normalization warp and fixed self-normalization warp are shifted upwards by for proper illustration).

The fixed self-normalization warps obtained from the offline BISN w/MS-BTS algorithm are also superimposed on the averaged self-normalization warp graph.

We give the variation of instantaneous self-normalization warp and recursively averaged self-normalization warp for a comparison in Figure 5.

The canonical HMMs are trained from warped features which are extracted using appropriate self-normalization warps.

The self-normalization warp for the incoming utterance is recursively estimated from earlier utterances.

Shao [7] showed a self-normalization large deviation result for without any moment conditions.

Determine the best self-normalization warp (i.e., the instantaneous warp for the current utterance ).