Module 5

The technique commonly used to remove noise from speech signals is

• FFT (Fast Fourier Transform)

• FIR (Finite Impulse Response) filter

• Convolutional neural network (CNN)

• Principal Component Analysis (PCA)

How do machine learning techniques contribute to the classification of biomedical signals?

• A) By increasing signal noise

• B) By reducing signal complexity

• C) By identifying patterns and abnormalities

• D) By ignoring signal variations

What role does the language model play in speech recognition?

• A) Converts audio signals to text

• B) Maps phonemes to words

• C) Determines the likelihood of word sequences

• D) Segments speech into phonemes

Which technique is used to remove periodic noise, such as hum or buzz, from speech signals?

• A) Wavelet transform

• B) Kalman filtering

• C) Notch filter

• D) Median filtering

The feature extraction technique commonly used for analyzing ECG signals is

• A) Fourier transform

• B) Principal Component Analysis (PCA)

• C) Wavelet transform

• D) Laplacian transform

Which machine learning approach is commonly used for automatic speech recognition (ASR)?

• A) Reinforcement learning

• B) Supervised learning

• C) Unsupervised learning

• D) Semi-supervised learning

What is the primary task in speech recognition?

• A) Segmenting speech into phonemes

• B) Converting speech to text

• C) Detecting background noise in speech signals

• D) Analyzing intonation patterns in speech

Which machine learning algorithm is commonly used for the detection of abnormalities in biomedical signals?

• A) Linear regression

• B) K-nearest neighbors (KNN)

• C) Random forest

• D) Convolutional neural network (CNN)

How can data augmentation techniques improve the performance of denoising models for speech signals?

• A) By reducing the amount of training data required

• B) By increasing the diversity of training samples

• C) By decreasing the computational complexity of the model

• D) By limiting the impact of input noise levels

Which loss function is commonly used to train denoising models for speech signals?

• A) Mean Squared Error (MSE)

• B) Cross-entropy loss

• C) KL divergence

• D) Huber loss