Sentence examples for talking conditions from inspiring English sources

Subjects with predisability had slower gait velocity and shorter stride length on both the normal and walking while talking conditions at baseline compared to nondisabled subjects.

However, there was no significant pattern of fluctuations across the six sessions on the three selected gait variables comparing the two groups during normal walking as well as on the walking while talking conditions.

In this corpus, eight sentences were generated under each of the neutral and shouted talking conditions.

The total number of utterances in both sessions under both talking conditions was 7200.

SUSAS database was designed originally for speech recognition under neutral and stressful talking conditions [30].

Figure 3 illustrates speaker identification performance in each of the neutral and angry talking conditions using SUSAS database based on each of LTRSPHMM1s, LTRSPHMM2s, CSPHMM1s, and CSPHMM2s.

Angry talking condition has been used as an alternative to the shouted talking condition since the shouted talking condition cannot be entirely separated from the angry talking condition in our real life [8].

Speaker recognition systems in shouted talking environments can be used in criminal investigations to identify the suspected persons who uttered voice in a shouted talking condition and in the applications of talking condition recognition systems.

Talking condition recognition systems can be used in medical applications, telecommunications, law enforcement, and military applications [12].

This figure shows apparently that speaker identification performance based on each model is almost ideal in the neutral talking condition.

This table demonstrates that CSPHMM2s lead each of LTRSPHMM1s, LTRSPHMM2s, and CSPHMM1s in the angry talking condition.