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Answer :
Final answer:
True. Recurrent networks, also known as recurrent neural networks (RNNs), are well-suited for speech recognition tasks due to their ability to capture temporal dependencies in sequential data.
Explanation:
Recurrent networks, also known as recurrent neural networks (RNNs), are a type of artificial neural network that is particularly well-suited for sequential data processing. RNNs have the ability to retain information from previous steps in the sequence, making them effective for tasks such as speech recognition.
In speech recognition, the input is a sequence of audio samples, and the goal is to transcribe the spoken words into text. Recurrent networks can capture the temporal dependencies in the audio data and learn to recognize patterns that correspond to different phonemes or words.
This makes them a popular choice for speech recognition systems, as they can effectively model the sequential nature of speech and capture the context and dependencies between different sounds and words.
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