Part I. A New Learning Paradigm in Speech and Language Technology.- Chapter 1. RL+SLT: Emerging RL-Powered Speech and Language Technologies.- Chapter 2. Why is RL+SLT Important, Now and How?.- Part II. Bandits and Reinforcement Learning: A Gentle Introduction.

- Chapter 3. Introduction to the Bandit Problems.- Chapter 4. Reinforcement Learning: Preliminaries and Terminologies.- Chapter 5. The RL Toolkit: A Spectrum of Algorithms.- Chapter 6. Inverse Reinforcement Learning Problem.

- Chapter 7. Behavioral Cloning and Imitation Learning.- Part III. Reinforcement Learning in SLT Applications.- Chapter 8. Reinforcement Learning Formulations for Speech and Language Applications.- Chapter 9. Reinforcement Learning in Automatic Speech Recognition (ASR): The Voice-First Revolution.

- Chapter 10. Reinforcement Learning in Speaker Recognition and Diarization: Decoding the Voices in the Crowd.- Chapter 11. Reinforcement Learning in Natural Language Understanding (NLU): Teaching Machines to Comprehend.- Chapter 12. Reinforcement Learning in Spoken Language Understanding (SLU): Giving Machines an Ear for Understanding.- Chapter 13. Reinforcement Learning in Text-to-Speech (TTS) Synthesis: Giving Machines a Voice.

- Chapter 14. Reinforcement Learning in Natural Language Generation (NLG): Machines as Wordsmiths.- Chapter 15. Reinforcement Learning in Large Language Models (LLM): The Rise of AI Language Giants.- Chapter 16. Reinforcement Learning in Conversational Recommendation Systems (CRS): AI's Personal Touch.- Part IV. Advanced Topics and Future Avenues.

- Chapter 17. Emerging Strategies in Reinforcement Learning Methods.- Chapter 18. Navigating the Frontiers: Key Challenges and Opportunities in RL-Powered Speech and Language Technology.- Chapter 19. Reflections, Resources, and Future Horizons in RL+SLT.