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
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Author : Marlene Welch
language : en
Publisher: Jaroslav Zdanovic
Release Date : 2025-03-31
Python Speaks A Guide To Developing Voice Controlled Apps With Speech Recognition written by Marlene Welch and has been published by Jaroslav Zdanovic this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Computers categories.
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
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Author : Tanay Pant
language : en
Publisher: Apress
Release Date : 2016-07-27
Building A Virtual Assistant For Raspberry Pi written by Tanay Pant and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-27 with Computers categories.
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
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Author : Dilyan Grigorov
language : en
Publisher: Springer Nature
Release Date : 2024-10-22
Introduction To Python And Large Language Models written by Dilyan Grigorov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-22 with Computers categories.
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.
Speech And Language Processing
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Author : Daniel Jurafsky
language : en
Publisher:
Release Date : 2000-01
Speech And Language Processing written by Daniel Jurafsky and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01 with Automatic speech recognition categories.
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.
Hands On Natural Language Processing With Python
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Author : Rajesh Arumugam
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-07-18
Hands On Natural Language Processing With Python written by Rajesh Arumugam and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-18 with Computers categories.
Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.
Deep Learning For Nlp And Speech Recognition
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Author : Uday Kamath
language : en
Publisher: Springer
Release Date : 2019-06-10
Deep Learning For Nlp And Speech Recognition written by Uday Kamath and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-10 with Computers categories.
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Professional Android Sensor Programming
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Author : Greg Milette
language : en
Publisher: John Wiley & Sons
Release Date : 2012-05-18
Professional Android Sensor Programming written by Greg Milette and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-18 with Computers categories.
Learn to build human-interactive Android apps, starting with device sensors This book shows Android developers how to exploit the rich set of device sensors—locational, physical (temperature, pressure, light, acceleration, etc.), cameras, microphones, and speech recognition—in order to build fully human-interactive Android applications. Whether providing hands-free directions or checking your blood pressure, Professional Android Sensor Programming shows how to turn possibility into reality. The authors provide techniques that bridge the gap between accessing sensors and putting them to meaningful use in real-world situations. They not only show you how to use the sensor related APIs effectively, they also describe how to use supporting Android OS components to build complete systems. Along the way, they provide solutions to problems that commonly occur when using Android's sensors, with tested, real-world examples. Ultimately, this invaluable resource provides in-depth, runnable code examples that you can then adapt for your own applications. Shows experienced Android developers how to exploit the rich set of Android smartphone sensors to build human-interactive Android apps Explores Android locational and physical sensors (including temperature, pressure, light, acceleration, etc.), as well as cameras, microphones, and speech recognition Helps programmers use the Android sensor APIs, use Android OS components to build complete systems, and solve common problems Includes detailed, functional code that you can adapt and use for your own applications Shows you how to successfully implement real-world solutions using each class of sensors for determining location, interpreting physical sensors, handling images and audio, and recognizing and acting on speech Learn how to write programs for this fascinating aspect of mobile app development with Professional Android Sensor Programming.
Kinect For Windows Sdk Programming Guide
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Author : Abhijit Jana
language : en
Publisher: Packt Publishing Ltd
Release Date : 2012-01-01
Kinect For Windows Sdk Programming Guide written by Abhijit Jana and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-01 with Computers categories.
This book is a practical tutorial that explains all the features of Kinect SDK by creating sample applications throughout the book. It includes a detailed discussion of APIs with step-by-step explanation of development of a real-world sample application. The purpose of this book is to explain how to develop applications using the Kinect for Windows SDK. If you are a beginner and looking to start developing applications using the Kinect for Windows SDK, and if you want to build motion-sensing, speech-recognizing applications with Kinect, this book is for you. This book uses C♯ and WPF (Windows P.
Hands Free Python Mastering Voice Control And Speech Recognition For Application Development
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Author : Omer Greene
language : en
Publisher: MIECO LLC
Release Date : 2025-04-03
Hands Free Python Mastering Voice Control And Speech Recognition For Application Development written by Omer Greene and has been published by MIECO LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-03 with Computers categories.
Discover the future of programming with Hands-Free Python, a revolutionary guide that takes you into the world of voice control and speech recognition. This book is designed for developers and tech enthusiasts eager to explore the cutting-edge capabilities of Python in the realm of voice-activated applications. Imagine creating sophisticated applications that respond to your voice commands, making the development process more intuitive and efficient than ever before. Throughout the book, you will uncover a wealth of content that transforms your understanding of Python programming. From the basics of setting up voice recognition tools to advanced techniques for integrating speech-to-text and text-to-speech functionalities, Hands-Free Python covers it all. Each chapter builds on the previous one, ensuring a comprehensive learning experience that takes you from novice to expert. The book tackles the common challenges faced by developers when working with voice-controlled applications. It provides practical solutions to issues such as handling background noise, improving accuracy in speech recognition, and optimizing the performance of voice-activated systems. By addressing these problems head-on, Hands-Free Python equips you with the knowledge and skills to create seamless and reliable voice-controlled applications.
Deep Learning With Applications Using Python
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Author : Navin Kumar Manaswi
language : en
Publisher: Apress
Release Date : 2018-04-04
Deep Learning With Applications Using Python written by Navin Kumar Manaswi and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-04 with Computers categories.
Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning. This book covers convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. What You Will Learn Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn. Use face recognition and face detection capabilities Create speech-to-text and text-to-speech functionality Engage with chatbots using deep learning Who This Book Is For Data scientists and developers who want to adapt and build deep learning applications.