Sentence examples for variable tone from inspiring English sources

Exact(1)

It is fascinating that, whatever their origin, the Middle Eastern and South Asian theories produced highly variable tone systems while the two ends of the old continent (i.e., the West and China) generated 12 tones based on a cycle of pitches 5 tones apart (such as C to G to D in the West).

Similar(59)

At a news conference here Tuesday afternoon, Russia's manager, Leonid Slutsky, and one of its top players, Artem Dzyuba, struck variable tones.

In addition, for the 4-hr moving average exposure, the variance of latent Parasympathetic Tone variable was higher (1.720; 95% PI: 1.535 to 1.921) compared to the variance of the latent Traffic variable (0.137; 95% PI: 0.112 to 0.165).

Between 25 and 30°C, the basal temperature was essentially variable, the vasomotor tone of the tail oscillating over time between vasoconstriction and vasodilatation phases (See Supporting Video S1).

Between 25 and 30°C, the basal temperature of the tail was essentially variable, the vasomotor tone of the tail oscillating over time between vasoconstriction and vasodilatation phases (see Supporting Video S1).

In other words, even though in these languages the conscious experience of the speakers may highlight only one discrete variable, length or tone, at a time, the results indicate that from the point of view of the processing system, the contrastive categories of tone and quantity may be based on the same simultaneously co-varying properties of the speech signal.

The HRV markers HF, SDNN and rMSSD were used as the markers for the latent Parasympathetic tone variable.

After a variable time period an identical tone was heard, signalling participants to stop counting their heartbeats and to enter their heartbeat estimate.

When you wear it, on a lanyard around your neck, it tracks your location; it also measures, every sixteen milliseconds, a variety of interpersonal variables, including "the tone of voice used; whether people face one another while talking; how much they gesture; and how much they talk, listen, and interrupt each other".

Narratives were quantified for 15 linguistic (e.g., negative emotion words) and six conceptual (e.g., affective tone) variables.

Microsoft stated that it was able to "significantly reduce accuracy differences across the demographics" by expanding facial recognition training data sets, initiating new data collection around the variables of skin tone, gender and age and improving its gender classification system by "focusing specifically on getting better results for all skin tones".

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