What are the advantages of deep learning-based speech recognition algorithms?

• A.Forced alignment of annotated data
• B.Automated feature extraction
• C.End-to-end task processing
• D.No data training

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Which of the following statements about the levels of natural language understanding are true?

• A.Syntactic analysis is to find out the meaning of words, structural meaning, their combined meaning, so as to determine the true meaning or concept expressed by a language.
• B.Semantic analysis is to analyze the structure of sentences and phrases to find out the relationship between words and phrases, as well as their functions in sentences.
• C.Speech analysis involves distinguishing independent phonemes from a speech stream based on phoneme rules, and then identifying syllables and their lexemes or words according to the phoneme form rules.
• D.Lexical analysis is to find the lexemes of a word and obtain linguistic information from them.
• E.Pragmatic analysis is to study the influence of the language's external environment on the language users.

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Which of the following statements about the functions of layer normalization and residual connection in the Transformer is true?

• A.Residual connections and layer normalization help prevent vanishing gradients and exploding gradients in deep networks.
• B.Residual connections primarily add depth to the model but do not aid in gradient propagation.
• C.Layer normalization accelerates model convergence and does not affect model stability.
• D.In shallow networks, residual connections are beneficial, but they aggravate the vanishing gradient problem in deep networks.

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Among image preprocessing techniques, gamma correction is a common non-linear brightness adjustment method. Which of the following statements are true about the application and features of gamma correction?

• A.Gamma correction applies only to grayscale images and does not apply to color images.
• B.Gamma correction is an enhancement technique based on exponential transformation mapping. It is used for non-linear contrast stretching.
• C.When # < 1, the input high grayscale range is compressed, and the low grayscale range is stretched, enhancing the dark areas while compressing the bright areas.
• D.When # > 1, the input low grayscale range is compressed, and the high grayscale range is stretched, enhancing the bright areas while compressing the dark areas.

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If OpenCV is used to read an image and save it to variable "img" during image preprocessing, (h, w) = img.
shape[:2] can be used to obtain the image size.

• A.TRUE
• B.FALSE

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