Python Speaks A Guide To Developing Voice Controlled Apps With Speech Recognition
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Python Speaks: A Guide to Developing Voice-Controlled Apps with Speech Recognition
Discover the future of technology with Python Speaks, your comprehensive guide to developing cutting-edge voice-controlled applications using speech recognition. This book takes you on a journey through the fascinating world of voice interfaces, equipping you with the skills and knowledge to create innovative and interactive applications. Whether you're a seasoned developer or a curious beginner, this guide provides the tools and techniques needed to harness the power of voice in your projects. The book begins with an exploration of the fundamental concepts behind speech recognition technology, offering a clear and concise introduction to the basics. You'll learn about the history and evolution of voice interfaces, understanding how they have transformed the way we interact with devices. The initial chapters lay a solid foundation, ensuring you have a strong grasp of the underlying principles before diving into more complex topics. As you progress, Python Speaks delves into the practical aspects of developing voice-controlled applications. Detailed explanations and step-by-step tutorials walk you through the process of integrating speech recognition into your Python projects. You'll explore various libraries and tools, gaining hands-on experience with real-world examples and exercises. From basic voice commands to advanced natural language processing, this guide covers it all.
Building a Virtual Assistant for Raspberry Pi
Build a voice-controlled virtual assistant using speech-to-text engines, text-to-speech engines, and conversation modules. This book shows you how to program the virtual assistant to gather data from the internet (weather data, data from Wikipedia, data mining); play music; and take notes. Each chapter covers building a mini project/module to make the virtual assistant better. You'll develop the software on Linux or OS X before transferring it to your Raspberry Pi, ready for deploying in your own home-automation or Internet of Things applications. Building a Virtual Assistant for Raspberry Pi walks you through various STTs and TTSs and the implementation of these components with the help of Python. After that you will start implementing logic for handling user queries and commands, so that the user can have conversations with Melissa. You will then work to improve logic handling to detect what the user wants Melissa to do. You will also work on building some useful applications/modules for Melissa, which will allow you to gain interesting information from Melissa such as the time, weather information, and data from Wikipedia. You will develop a music playing application as well as a note taking application for Melissa, laying the foundations for how Melissa can be further extended. Finally, you will learn how to deploy this software to your Raspberry Pi and how you can further scale Melissa to make her more intelligent, interactive and how you can use her in other projects such as home automation as well. What You'll Learn Design the workflow and discover the concepts of building a voice controlled assistant Develop modules for having conversations with the assistant Enable the assistant to retrieve information from the internet Build utilities like a music player and a note taking application for the virtual assistant Integrate this software with a Raspberry Pi Who This Book Is For Anyone who has built a home automation project with Raspberry Pi and now want to enhance it by making it voice-controlled. The book would also interest students from computer science or related disciplines.
Introduction to Python and Large Language Models
Gain a solid foundation for Natural Language Processing (NLP) and Large Language Models (LLMs), emphasizing their significance in today’s computational world. This book is an introductory guide to NLP and LLMs with Python programming. The book starts with the basics of NLP and LLMs. It covers essential NLP concepts, such as text preprocessing, feature engineering, and sentiment analysis using Python. The book offers insights into Python programming, covering syntax, data types, conditionals, loops, functions, and object-oriented programming. Next, it delves deeper into LLMs, unraveling their complex components. You’ll learn about LLM elements, including embedding layers, feedforward layers, recurrent layers, and attention mechanisms. You’ll also explore important topics like tokens, token distributions, zero-shot learning, LLM hallucinations, and insights into popular LLM architectures such as GPT-4, BERT, T5, PALM, and others. Additionally, it covers Python libraries like Hugging Face, OpenAI API, and Cohere. The final chapter bridges theory with practical application, offering step-by-step examples of coded applications for tasks like text generation, summarization, language translation, question-answering systems, and chatbots. In the end, this book will equip you with the knowledge and tools to navigate the dynamic landscape of NLP and LLMs. What You’ll Learn Understand the basics of Python and the features of Python 3.11 Explore the essentials of NLP and how do they lay the foundations for LLMs. Review LLM components. Develop basic apps using LLMs and Python. Who This Book Is For Data analysts, AI and Machine Learning Experts, Python developers, and Software Development Professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks.