Emphasizing real-world applications, the book provides clear, step-by-step guidance on employing RL and bandit methods to address challenges in speech and language technology. It includes case studies and practical tips that equip readers to apply these methods to their own projects. As a timely and crucial resource, this book is ideal for speech and language researchers, engineers, students, and practitioners eager to enhance the performance of speech and language systems and to innovate with new interactive learning paradigms from an interface design perspective.
- Provides a comprehensive survey of reinforcement learning methods tailored to speech and language technology;
- Discusses real-world application studies such as ASR, TTS, large language models, and conversational systems;
- Covers emerging trends in deep reinforcement learning, multi-agent systems, and transfer learning.
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