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Huawei HCIP-AI-EI Developer V2.5 Sample Questions:

1. Mel-frequency cepstral coefficients (MFCCs) take into account human auditory characteristics by first mapping the linear spectrum to the Mel nonlinear spectrum based on auditory perception, and then converting it to the cepstral domain.

A) FALSE
B) TRUE

2. John wants to deploy a large model locally to implement the Q&A assistant function for his company. Which of the following factors is unnecessary for John to consider?

A) Demand for computing power
B) Output delay
C) Model security
D) Model development framework

3. In NLP tasks, transformer models perform well in multiple tasks due to their self-attention mechanism and parallel computing capability. Which of the following statements about transformer models are true?

A) Transformer models outperform RNN and CNN in processing long texts because they can effectively capture global dependencies.
B) Multi-head attention is the core component of a transformer model. It computes multiple attention heads in parallel to capture semantic information in different subspaces.
C) A transformer model directly captures the dependency between different positions in the input sequence through the self-attention mechanism, without using the recurrent neural network (RNN) or convolutional neural network (CNN).
D) Positional encoding is optional in a transformer model because the self-attention mechanism can naturally process the order information of sequences.

4. Which of the following has never been used as a method in the history of NLP?

A) Statistics-based method
B) Rule-based method
C) Recursion-based method
D) Deep learning-based method

5. Which of the following is not an acoustic feature of speech?

A) Duration
B) Semantics
C) Amplitude
D) Frequency

Solutions: