Sentence examples for speakers identification from inspiring English sources

The old approaches in speaker recognition are developed for speakers' identification and verification in a speech sample pronounced by one person.

Source separation is a very important step for human-robot interaction: it allows latter tasks like speakers identification, speech and motion recognition and environmental sound analysis to be achieved properly.

In particular, the initial 30 speakers (identification numbers: 01 to 30), the next 30 speakers (31 to 60) and the last 30 speakers (61 to 90) were used for the background, development and test databases.

In particular, the initial 20 speakers (identification numbers: 01 to 04, 09 to 20, 22, 25, 26, 28), the next 20 speakers (29 to 48) and the last 20 speakers (49 to 68) were used for the background, development and test databases.

In addition, putting a camera in a car means that automakers could potentially add face and speaker identification software.

However, method 2 proposed in [22] degraded the speaker identification performance in the speaker identification field.

Distinguishing them is therefore a challenge in speaker identification.

Figure 7 Average speaker identification rates using different training sets.

Speaker identification performance is almost perfect in neutral talking environments.

The speaker identification accuracies are shown in Figure 4.

Table 3 gives the conditions for speaker identification.