Sentence examples for voice recognizer from inspiring English sources

Settings screen - provides settings of behavior of the two basic components - synthesizer and voice recognizer (Fig. 4).

In the initialization method, import of settings from an external file is performed first and then the voice recognizer and synthesizer are set.

A low, medium, high or expert level is assigned using these measures; Most frequent objective of the user; Reference to the location of all the information regarding the previous interactions and the corresponding objective and subjective parameters for that user; Parameters of the user neutral voice as explained in "The emotion recognizer" section.

Once the cross-lingual adaptation is carried out, a second step is performed to adapt the recognizer trained with common voices to detect impaired speech.

Recognition presupposes a subject of recognition (the recognizer) and an object (the recognized).

We first review the main differences between speech and singing voice and present the basic structure of the phonetic recognizer architecture, and then the proposed singing adaptation methods and language models.

The emotion recognizer detects the user emotional state by extracting an emotion category from the voice signal and the dialogue history.

Meanwhile, a 2012 partnership with Panasonic saw the two firms teaming up to develop "NovaLite," a software automatic speech recognizer that would be offered to consumer electronic manufacturers who wanted to voice-enable their products.

A voice transformation technique which normalizes the children's speech signal before being fed to the adults' speech trained recognizer has been explored in [27].

From the blog post: Our Pig Latin Voice Search is even more fun than our other languages, because when you speak in Pig Latin, our speech recognizer not only recognizes your piggy speech but also translates it automagically to normal English and does a Google search.

Today, speaker-independent and phoneme HMM-based speech recognizers are being included in mobile devices, and voice-tag technologies are mature enough to leverage the existing computational resources and algorithms from the speaker-independent speech recognizer for further efficiency.