H13-321_V2.5 Exam Dumps - HCIP - AI EI Developer V2.5 Exam

In hybridDNN-HMMspeech recognition:

TheDNNacts as an acoustic model, transforming audio features into probability estimates for phonetic states.

TheHMMmodels the temporal sequence and transitions between phonetic states, handling time dependencies and variability in speech.

This combination leverages the representational power of DNNs and the sequence modeling strengths of HMMs.

Exact Extract from HCIP-AI EI Developer V2.5:

"In DNN-HMM systems, the DNN outputs state posterior probabilities, and the HMM models the temporal sequence structure of speech."

NER(Named Entity Recognition) is a core NLP task that involves locating and categorizing entities within text into predefined categories like persons, organizations, places, dates, monetary values, and percentages. NER is widely used in information extraction, question answering, and knowledge graph construction.

Exact Extract from HCIP-AI EI Developer V2.5:

"NER identifies and classifies named entities in text into categories such as person names, organizations, locations, time expressions, and numeric values."

TheTransformerarchitecture introduced in 2017 eliminates recurrence (RNN) and convolution entirely, relying solely on self-attention mechanisms and feed-forward layers. It does not contain LSTM or CNN components, which distinguishes it from previous sequence models.

Exact Extract from HCIP-AI EI Developer V2.5:

"The Transformer architecture does not use RNNs or CNNs. It relies entirely on self-attention and feed-forward networks for sequence modeling."

Gamma correction is anon-linearimage processing method used to adjust brightness and contrast. It is not limited to grayscale images — it can be applied to both grayscale and color images by operating on individual channels.

γ <</b> 1:Enhances dark regions (brightens shadows) and compresses highlights.

γ > 1:Enhances bright regions and compresses dark regions.It is based onpower-law (exponential) transformation, making it effective for adjusting human-perceived luminance.

Exact Extract from HCIP-AI EI Developer V2.5:

"Gamma correction is a non-linear brightness adjustment based on power-law transformation. It applies to both grayscale and color images. For γ<</i>1, dark regions are brightened; for γ>1, bright regions are enhanced."