Sentence examples for temporal voice from inspiring English sources

This study analyzed temporal voice therapy data (duration and frequency) as reported in the scientific literature between 1975 and May 2013.

We examined ASD-related differences in the activation and connectivity of brain areas involved in the processing of facial, vocal and audiovisual social signals (i.e. fusiform face area (FFA), temporal voice area (TVA), and amygdala; Refs. (Brück et al., 2011; Wicker et al., 2008)).

Participants were first scanned in a 10 min "voice localizer" in order to localize the temporal voice areas (TVA).

The human brain contains temporal voice areas (TVA) [ 1] involved in an acoustic-based representation of voice identity [ 2 6], but the underlying coding mechanisms remain unknown.

The voice localizer (TR = 2 s; TE = 30 ms; 310 volumes; 10 min) allows reliable identification of the temporal voice areas (TVAs) using the vocal versus non-vocal contrast.

Converging evidence for the involvement of specific cortical regions, including the temporal voice areas (TVAs), in voice gender recognition is, however, still missing (Lattner et al. 2005; Sokhi et al. 2005).

In addition, we hypothesize that over-activation of either the STG or IP / temporal lobe voice representations could result in hearing voices or in the feeling that someone is speaking.

The well-known social withdrawal of children with ASD has been attributed lately to deficits in the superior temporal sulcus voice selective regions: hearing and processing impairments based on developmental biological deficits could lead to social withdrawal [17].

This study analyzed the temporal changes of voice quality after thyroidectomy and assessed the predictive perioperative parameters of postthyroidectomy voice disorder (PTVD).

There exist possibilities that some useful attributes can be harvested from the time domain considering the temporal patterns of voice data that are supposedly distinctive from one another.

Further, the choice of using linear approximations to model temporal information within voiced speech segments, while the simplest, may not be optimal and is an avenue for future work.