Abstract
In this chapter, we investigate deep reinforcement learning for text and speech applications. Reinforcement learning is a branch of machine learning that deals with how agents learn a set of actions that can maximize expected cumulative reward. In past research, reinforcement learning has focused on game play. Recent advances in deep learning have opened up reinforcement learning to wider applications for real-world problems, and the field of deep reinforcement learning was spawned. In the first part of this chapter, we introduce the fundamental concepts of reinforcement learning and their extension through the use of deep neural networks. In the latter part of the chapter, we investigate several popular deep reinforcement learning algorithms and their application to text and speech NLP tasks.
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Kamath, U., Liu, J., Whitaker, J. (2019). Deep Reinforcement Learning for Text and Speech. In: Deep Learning for NLP and Speech Recognition . Springer, Cham. https://doi.org/10.1007/978-3-030-14596-5_13
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DOI: https://doi.org/10.1007/978-3-030-14596-5_13
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