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Artificial Neural Networks, in the context of Speech Recognition, refer to computational models inspired by the human brain's interconnected neurons. These networks learn patterns and structures from data, making them highly effective for speech recognition tasks. They can model complex non-linear relationships between input features (like sound waves) and output labels (like spoken words), enabling high accuracy in speech recognition systems. This aligns with the broader categories of Technology, Artificial Intelligence, and Artificial Intelligence Algorithms, as it represents a specific technique within AI for processing information and solving problems.