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*Acoustic modeling* is a crucial step in speech recognition. It involves training a model to map acoustic features to phonemes, which are the basic units of speech. Deep learning models, such as deep neural networks (DNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), are commonly used for acoustic modeling. These models learn complex patterns in the audio data, enabling them to accurately identify phonemes even in noisy environments.
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