Sentence examples for level recognizer from inspiring English sources

The baseline system was initially designed as a phoneme level recognizer with three active states, one Gaussian per state, continuous, left-to-right, and no skip HMM models.

In computer vision, we get tantalizing glimpses of what the deep networks are actually doing: we can identify line recognizers at one level, then, say, eye and nose recognizers at a higher level, followed by face recognizers above that and finally whole person recognizers.

Another test was carried out to verify the functionality of the proposed two-level architecture comprising the gender recognizer and of the emotional speech classifier.

As shown in Table 2, our CRF-based entity recognizer yields entity-level precision values that range from 87.60% (TARGET) to 93.00% (EXPO).

Performance of the recognizer at the token level, include precision values ranging from 90.06% (TARGET) to 98.10% (EXPO), while recall values range from 85.50% (EXPO) to 94.30% (NANO).

The second level refines the detection further using a speech recognizer and a query-driven decoding algorithm.

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

Oishi et al. [42] uses a DTW-based search at the HMM state-level from syllables obtained from a word-based speech recognizer and a deep neural network (DNN) posteriorgram-based rescoring, and [43] adds a logistic regression-based approach for detection rescoring.

Obara et al. [44] employs a syllable-based speech recognizer and dynamic programming at the triphone-state level to output detections and DNN posteriorgram-based rescoring.

As in the intention recognizer, the user simulation generates the user intention level, that is, the user simulator provides concepts and attributes that represent the intention of the user utterance.

The second level refines the detection on the selected segments, by using a speech recognizer based on a query-driven decoding algorithm.