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This book presents a number of studies which focus on the [voice] grammar of Japanese, paying particular attention to historical background, dialectal diversity, phonetic experiment, and phonological analysis. Both voicing processes in consonants (such as Sequential Voicing, or Rendaku) and vowels (such as vowel devoicing) are examined. A number of new analyses are presented, focusing on well-known data that have been controversial in phonological debate in the past, but also presenting new (or rediscovered) data, partly through the work of Japanese scholars that hitherto went mostly unnoticed, partly through new database research, and partly through phonetic experiment.
The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater
This book takes readers back and forth through time and makes the past accessible to all families, students and the general reader and is an unprecedented collection of a list of events in chronological order and a wealth of informative knowledge about the rise and fall of empires, major scientific breakthroughs, groundbreaking inventions, and monumental moments about everything that has ever happened.
Get a step-by-step guide for developing voice interfaces for applications and devices connected to the Internet of Things. By allowing consumers to use natural human interactions, you can avoid awkward methods of input and interactivity to provide them with elevated user experiences. This practical book is ideal for software engineers who build applications for the Web, smartphones, as well as embedded systems that dominate the IoT space. Integrate voice interfaces with internet connected devices and sensors Learn how to integrate with existing voice interfaces Understand when to use a voice over other Natural User Interface technologies Build a prototype with tools such as Raspberry Pi, solderless breadboards, jumper cables, sensors, Arduino, Visual Studio, and other tools Use cloud services such as Azure and AWS to integrate voice with your existing or new web service end-points
What Is Speech Recognition Computer science and computational linguistics have spawned a subfield known as speech recognition, which is an interdisciplinary field that focuses on the development of methodologies and technologies that enable computers to recognize and translate spoken language into text. The primary advantage of this is that the text can then be searched. Automatic speech recognition, sometimes abbreviated as ASR, is another name for it, as is computer speech recognition and voice to text (STT). The domains of computer science, linguistics, and computer engineering are all represented in its incorporation of knowledge and study. Speech synthesis is the process of doing things...
Extraordinary advances in machine translation over the last three quarters of a century have profoundly affected many aspects of the translation profession. The widespread integration of adaptive “artificially intelligent” technologies has radically changed the way many translators think and work. In turn, groundbreaking empirical research has yielded new perspectives on the cognitive basis of the human translation process. Translation is in the throes of radical transition on both professional and academic levels. The game-changing introduction of neural machine translation engines almost a decade ago accelerated these transitions. This volume takes stock of the depth and breadth of resulting developments, highlighting the emerging rivalry of human and machine intelligence. The gathering and analysis of big data is a common thread that has given access to new insights in widely divergent areas, from literary translation to movie subtitling to consecutive interpreting to development of flexible and powerful new cognitive models of translation.
This is an open access book. The 2022 3rd International Conference on Artificial Intelligence and Education(ICAIE 2022) will be held in Chengdu, China during June 24-26, 2022. The meeting focused on the new trends in the development of "artificial intelligence" and "education" under the new situation, and jointly discussed how to empower and promote the high-quality development of "artificial intelligence" and "education". An ideal platform to share views and experiences with industry experts. The conference invites experts and scholars in the field to conduct wonderful exchanges based on their own research results based on the development of the times. The themes are around artificial intelligence technology and applications; intelligent and knowledge-based systems; information-based education; intelligent learning; advanced information theory and neural network technology ; software computing and algorithms; intelligent algorithms and computing and many other topics.
This book focuses on the basics of natural language processing and machine learning required to make a standard speech- based gender identification system. In this book all the required signal processing techniques required for understanding the basics of natural language processing including all types of Fourier transform, basic speech enhancement techniques, voice activity detection and pitch estimation using sub harmonic-to-harmonic ratio are briefly explained as well. In the machine learning part, all the relevant machine learning models like Support Vector Machines, Gaussian Mixture Models and Adaptive boosting are explained. Lastly the results of different gender identification systems that were implemented using state of the art techniques are portrait and analysed.
This volume contains the Proceedings of the 7th International Conference on Text, Speech and Dialogue, held in Brno, Czech Republic, in September 2004, under the auspices of the Masaryk University. This series of international conferences on text, speech and dialogue has come to c- stitute a major forum for presentation and discussion, not only of the latest developments in academic research in these ?elds, but also of practical and industrial applications. Uniquely, these conferences bring together researchers from a very wide area, both intellectually and geographically, including scientists working in speech technology, dialogue systems, text processing, lexicography, and other related ?e...
Most data scientists and engineers today rely on quality labeled data to train machine learning models. But building a training set manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Wee Hyong Tok, Amit Bahree, and Senja Filipi show you how to create products using weakly supervised learning models. You'll learn how to build natural language processing and computer vision projects using weakly labeled datasets from Snorkel, a spin-off from the Stanford AI Lab. Because so many companies have pursued ML projects that never go beyond their labs, this book also provides a guide on how to ship the deep learning models you build. Get up to speed on the field of weak supervision, including ways to use it as part of the data science process Use Snorkel AI for weak supervision and data programming Get code examples for using Snorkel to label text and image datasets Use a weakly labeled dataset for text and image classification Learn practical considerations for using Snorkel with large datasets and using Spark clusters to scale labeling