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Learn OpenAI Whisper

Author : Josué R. Batista

Publisher : Packt Publishing Ltd

Page : 372 pages

File Size : 47,31 MB

Release : 2024-05-31

Category : Computers

ISBN : 1835087493

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Book Description

Master automatic speech recognition (ASR) with groundbreaking generative AI for unrivaled accuracy and versatility in audio processing Key Features Uncover the intricate architecture and mechanics behind Whisper's robust speech recognition Apply Whisper's technology in innovative projects, from audio transcription to voice synthesis Navigate the practical use of Whisper in real-world scenarios for achieving dynamic tech solutions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs the field of generative AI evolves, so does the demand for intelligent systems that can understand human speech. Navigating the complexities of automatic speech recognition (ASR) technology is a significant challenge for many professionals. This book offers a comprehensive solution that guides you through OpenAI's advanced ASR system. You’ll begin your journey with Whisper's foundational concepts, gradually progressing to its sophisticated functionalities. Next, you’ll explore the transformer model, understand its multilingual capabilities, and grasp training techniques using weak supervision. The book helps you customize Whisper for different contexts and optimize its performance for specific needs. You’ll also focus on the vast potential of Whisper in real-world scenarios, including its transcription services, voice-based search, and the ability to enhance customer engagement. Advanced chapters delve into voice synthesis and diarization while addressing ethical considerations. By the end of this book, you'll have an understanding of ASR technology and have the skills to implement Whisper. Moreover, Python coding examples will equip you to apply ASR technologies in your projects as well as prepare you to tackle challenges and seize opportunities in the rapidly evolving world of voice recognition and processing.What you will learn Integrate Whisper into voice assistants and chatbots Use Whisper for efficient, accurate transcription services Understand Whisper's transformer model structure and nuances Fine-tune Whisper for specific language requirements globally Implement Whisper in real-time translation scenarios Explore voice synthesis capabilities using Whisper's robust tech Execute voice diarization with Whisper and NVIDIA's NeMo Navigate ethical considerations in advanced voice technology Who this book is for Learn OpenAI Whisper is designed for a diverse audience, including AI engineers, tech professionals, and students. It's ideal for those with a basic understanding of machine learning and Python programming, and an interest in voice technology, from developers integrating ASR in applications to researchers exploring the cutting-edge possibilities in artificial intelligence.



The Computational Content Analyst

Author : Chris J. Vargo

Publisher : Taylor & Francis

Page : 140 pages

File Size : 33,65 MB

Release : 2024-12-02

Category : Language Arts & Disciplines

ISBN : 1040227201

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Book Description

Most digital content, whether it be thousands of news articles or millions of social media posts, is too large for the naked eye alone. Often, the advent of immense datasets requires a more productive approach to labeling media beyond a team of researchers. This book offers practical guidance and Python code to traverse the vast expanses of data—significantly enhancing productivity without compromising scholarly integrity. We’ll survey a wide array of computer-based classification approaches, focusing on easy-to-understand methodological explanations and best practices to ensure that your data is being labeled accurately and precisely. By reading this book, you should leave with an understanding of how to select the best computational content analysis methodology to your needs for the data and problem you have. This guide gives researchers the tools they need to amplify their analytical reach through the integration of content analysis with computational classification approaches, including machine learning and the latest advancements in generative artificial intelligence (AI) and large language models (LLMs). It is particularly useful for academic researchers looking to classify media data and advanced scholars in mass communications research, media studies, digital communication, political communication, and journalism. Complementing the book are online resources: datasets for practice, Python code scripts, extended exercise solutions, and practice quizzes for students, as well as test banks and essay prompts for instructors. Please visit www.routledge.com/9781032846354.



Machine Learning in Elixir

Author : Sean Moriarity

Publisher : Pragmatic Bookshelf

Page : 448 pages

File Size : 16,61 MB

Release : 2024-08-27

Category : Computers

ISBN :

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Book Description

Stable Diffusion, ChatGPT, Whisper - these are just a few examples of incredible applications powered by developments in machine learning. Despite the ubiquity of machine learning applications running in production, there are only a few viable language choices for data science and machine learning tasks. Elixir's Nx project seeks to change that. With Nx, you can leverage the power of machine learning in your applications, using the battle-tested Erlang VM in a pragmatic language like Elixir. In this book, you'll learn how to leverage Elixir and the Nx ecosystem to solve real-world problems in computer vision, natural language processing, and more. The Elixir Nx project aims to make machine learning possible without the need to leave Elixir for solutions in other languages. And even if concepts like linear models and logistic regression are new to you, you'll be using them and much more to solve real-world problems in no time. Start with the basics of the Nx programming paradigm - how it differs from the Elixir programming style you're used to and how it enables you to write machine learning algorithms. Use your understanding of this paradigm to implement foundational machine learning algorithms from scratch. Go deeper and discover the power of deep learning with Axon. Unlock the power of Elixir and learn how to build and deploy machine learning models and pipelines anywhere. Learn how to analyze, visualize, and explain your data and models. Discover how to use machine learning to solve diverse problems from image recognition to content recommendation - all in your favorite programming language. What You Need: You'll need a computer with a working installation of Elixir v1.12 and Erlang/OTP 24. For some of the more compute intensive examples, you'll want to use EXLA, which currently only supports x86-64 platforms. While not explicitly required, some examples will demonstrate programs running on accelerators such as CUDA/ROCm enabled GPUs and Google TPUs. Most of these programs will still run fine on a regular CPU, just for much longer periods of time.



Breaking the Language Barrier: Demystifying Language Models with OpenAI

Author : Rayan Wali

Publisher : Rayan Wali

Page : 301 pages

File Size : 14,82 MB

Release : 2023-03-08

Category : Computers

ISBN :

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Book Description

Breaking the Language Barrier: Demystifying Language Models with OpenAI is an informative guide that covers practical NLP use cases, from machine translation to vector search, in a clear and accessible manner. In addition to providing insights into the latest technology that powers ChatGPT and other OpenAI language models, including GPT-3 and DALL-E, this book also showcases how to use OpenAI on the cloud, specifically on Microsoft Azure, to create scalable and efficient solutions.



Routledge Handbook of Technological Advances in Researching Language Learning

Author : Karim Sadeghi

Publisher : Taylor & Francis

Page : 697 pages

File Size : 42,94 MB

Release : 2024-11-29

Category : Language Arts & Disciplines

ISBN : 1040165443

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Book Description

The Routledge Handbook of Technological Advances in Researching Language Learning is the first volume to bring together the extant scholarship on the nature and role of digital technology in conducting second language research. The Handbook showcases technological advances, including issues and considerations, affecting research conduction in second language education. The contributions focus on the role of digital technology in researching second language education, second language acquisition, and applied linguistics. Contributions by both seasoned and junior scholars feature empirical studies and methodological and/or theoretical discussions of technological tools used (or tools that can be used) for conducting research into various aspects of second language learning and acquisition. This book will primarily appeal to academic specialists, practitioners, and professionals in the field of applied linguistics and second language education. The book will also be informative for scholars and professionals in disciplines such as educational technology and TESOL.



The Sustainable Power Grid

Author : Brian D' Andrade

Publisher : Elsevier

Page : 272 pages

File Size : 10,82 MB

Release : 2024-10-22

Category : Technology & Engineering

ISBN : 0443134413

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Book Description

The Sustainable Power Grid provides a breakdown of the different challenges faced by power grid modernization and presents practical approaches to tackle them. The technologies, case studies, and applications are presented from the perspective of engineering consultants who participate in major grid-related disasters and perform detailed forensic investigations that support the evolution of sustainable power quality. Chapters discuss key issues surrounding extreme weather, power quality, new technologies, and power converters. This book also outlines a quantitative risk-based framework for asset health assessment of overhead lines, along with engineering and environmental considerations. Concluding with a deep dive into energy storage, topics consist of energy storage system protection, condition monitoring, and emerging technologies. Completely practical in nature, this is a valuable resource for engineers in the electrical power industry and offers students and researchers applied content in the latest power grid technologies. - Discusses major issues that face the modernization of the electric power grid, including new generation sources, safety, environmental impacts, and energy storage - Showcases real-world case studies and applications to bridge the gap between power grid theory and engineering - Presents new approaches to power grid problems such as security, availability, and reliability



Data Labeling in Machine Learning with Python

Author : Vijaya Kumar Suda

Publisher : Packt Publishing Ltd

Page : 398 pages

File Size : 37,43 MB

Release : 2024-01-31

Category : Computers

ISBN : 1804613789

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Book Description

Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labeling Key Features Generate labels for regression in scenarios with limited training data Apply generative AI and large language models (LLMs) to explore and label text data Leverage Python libraries for image, video, and audio data analysis and data labeling Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today’s data-driven world, mastering data labeling is not just an advantage, it’s a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution. With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively. By the end of this book, you’ll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data.What you will learn Excel in exploratory data analysis (EDA) for tabular, text, audio, video, and image data Understand how to use Python libraries to apply rules to label raw data Discover data augmentation techniques for adding classification labels Leverage K-means clustering to classify unsupervised data Explore how hybrid supervised learning is applied to add labels for classification Master text data classification with generative AI Detect objects and classify images with OpenCV and YOLO Uncover a range of techniques and resources for data annotation Who this book is for This book is for machine learning engineers, data scientists, and data engineers who want to learn data labeling methods and algorithms for model training. Data enthusiasts and Python developers will be able to use this book to learn data exploration and annotation using Python libraries. Basic Python knowledge is beneficial but not necessary to get started.



Endangered Languages

Author : Evangelia Adamou

Publisher : MIT Press

Page : 262 pages

File Size : 12,64 MB

Release : 2024-08-06

Category : Language Arts & Disciplines

ISBN : 0262548704

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Book Description

A concise, accessible introduction to language endangerment and why it is one of the most urgent challenges of our times. 58% of the world’s languages—or, approximately 4,000 languages—are endangered. When we break this figure down, we realize that roughly ten percent of languages have fewer than ten language keepers. And, if one language stops being used every three months, this means that in the next 100 years, if we do nothing, 400 more languages will become dormant. In Endangered Languages, Evangelia Adamou, a specialist of endangered languages and a learner of her own community language, Nashta, offers a sobering look at language endangerment and what is truly lost when a language disappears from usage. Combining recent advances from the Western scientific tradition—from the fields of linguistics, psycholinguistics, neurolinguistics, language attrition, population genetics, and natural language processing—and insights from Indigenous epistemology, theory, and ethics, Adamou examines a wealth of issues surrounding endangered languages. She discusses where endangered languages are found, including how they are faring in a digital world, why these languages are no longer used, and how communities can reclaim languages and keep them strong. Adamou also explains the impact of language continuity on community and individual health and well-being, the importance of language transmission in cultural transmission, and why language rights are essentially human rights. Drawing on varied examples from the Wampanoag Nation to Wales, Endangered Languages offers a powerful reminder of the crucial role every language has in the vitality and well-being of individuals, communities, and our world.



Smart University

Author : Lindsay Weinberg

Publisher : JHU Press

Page : 148 pages

File Size : 20,34 MB

Release : 2024-10-08

Category : Education

ISBN : 142145002X

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Book Description

How surveillance perpetuates long-standing injustices woven into the fabric of higher education. Higher education increasingly relies on digital surveillance in the United States. Administrators, consulting firms, and education technology vendors are celebrating digital tools as a means of ushering in the age of "smart universities." By digitally monitoring and managing campus life, institutions can supposedly run their services more efficiently, strengthen the quality of higher education, and better prepare students for future roles in the digital economy. Yet in practice, these initiatives often perpetuate austerity, structural racism, and privatization at public universities under the guise of solving higher education's most intractable problems. In Smart University, Lindsay Weinberg evaluates how this latest era of tech solutions and systems in our schools impacts students' abilities to access opportunities and exercise autonomy on their campuses. Using historical and textual analysis of administrative discourses, university policies, conference proceedings, grant solicitations, news reports, tech industry marketing materials, and product demonstrations, Weinberg argues that these more recent transformations are best understood as part of a longer history of universities supporting the development of technologies that reproduce racial and economic injustice on their campuses and in their communities. Aimed at anyone concerned with the future of surveillance on higher education, Smart University empowers readers with the knowledge, tools, and frameworks for contesting and reimagining the role of digital technology on university campuses.