This book provides the readers with retrospective and prospective views with detailed explanations of component technologies, speech recognition, language translation and speech synthesis. Speech-to-speech translation system (S2S) enables to break language barriers, i.e., communicate each other between any pair of person on the glove, which is one of extreme dreams of humankind. People, society, and economy connected by S2S will demonstrate explosive growth without exception. In 1986, Japan initiated basic research of S2S, then the idea spread world-wide and were explored deeply by researchers during three decades. Now, we see S2S application on smartphone/tablet around the world. Computational resources such as processors, memories, wireless communication accelerate this computation-intensive systems and accumulation of digital data of speech and language encourage recent approaches based on machine learning. Through field experiments after long research in laboratories, S2S systems are being well-developed and now ready to utilized in daily life. Unique chapter of this book is end-2-end evaluation by comparing system’s performance and human competence. The effectiveness of the system would be understood by the score of this evaluation. The book will end with one of the next focus of S2S will be technology of simultaneous interpretation for lecture, broadcast news and so on.

Verbmobil is the result of eight years of intensive research in a large speech-to-speech translation project, executed by a consortium comprising nineteen academic and four industrial partners. The system that was developed by more than 100 researchers and engineers handles dialogs in three business-oriented domains, with translation between three languages: German, English, and Japanese. Verbmobil deals with spontaneous speech, which includes realistic repair phenomena, and uses deep semantic analysis to recognize a speaker's slips and to translate what he tried to say rather than what he actually said. - This book gives the first comprehensive overview of the results of this unique and seminal project in human language technology. Contributions by leading scientists in speech and language technology look at the component technologies that make Verbmobil the most advanced speech-to-speech translation system worldwide and a landmark project in the history of natural language processing.

Automatic Speech Translation introduces recent results of Japanese research and development in speech translation and speech recognition. Topics covered include: fundamental concepts of speech recognition; speech pattern representation; phoneme-based HMM phoneme recognition; continuous speech recognition; speaker adaptation; speaker-independent speech recognition; utterance analysis, utterance transfer, utterance generation; contextual process­ing; speech synthesis and an experimental system of speech translation. This book presents the complicated technological aspects of machine translation and speech recognition, and outlines the future directions of this rapidly developing area of technology.

Tanja Schultz and Katrin Kirchhoff have compiled a comprehensive overview of speech processing from a multilingual perspective. By taking this all-inclusive approach to speech processing, the editors have included theories, algorithms, and techniques that are required to support spoken input and output in a large variety of languages. Multilingual Speech Processing presents a comprehensive introduction to research problems and solutions, both from a theoretical as well as a practical perspective, and highlights technology that incorporates the increasing necessity for multilingual applications in our global community. Current challenges of speech processing and the feasibility of sharing data and system components across different languages guide contributors in their discussions of trends, prognoses and open research issues. This includes automatic speech recognition and speech synthesis, but also speech-to-speech translation, dialog systems, automatic language identification, and handling non-native speech. The book is complemented by an overview of multilingual resources, important research trends, and actual speech processing systems that are being deployed in multilingual human-human and human-machine interfaces. Researchers and developers in industry and academia with different backgrounds but a common interest in multilingual speech processing will find an excellent overview of research problems and solutions detailed from theoretical and practical perspectives. - State-of-the-art research with a global perspective by authors from the USA, Asia, Europe, and South Africa - The only comprehensive introduction to multilingual speech processing currently available - Detailed presentation of technological advances integral to security, financial, cellular and commercial applications

Introduces the integration of theoretical and applied translation studies for socially-oriented and data-driven empirical translation research.

Speech--to--Speech Translation: a Massively Parallel Memory-Based Approach describes one of the world's first successful speech--to--speech machine translation systems. This system accepts speaker-independent continuous speech, and produces translations as audio output. Subsequent versions of this machine translation system have been implemented on several massively parallel computers, and these systems have attained translation performance in the milliseconds range. The success of this project triggered several massively parallel projects, as well as other massively parallel artificial intelligence projects throughout the world. Dr. Hiroaki Kitano received the distinguished `Computers and Thought Award' from the International Joint Conferences on Artificial Intelligence in 1993 for his work in this area, and that work is reported in this book.

In 1992 it seemed very difficult to answer the question whether it would be possible to develop a portable system for the automatic recognition and translation of spon taneous speech. Previous research work on speech processing had focused on read speech only and international projects aimed at automated text translation had just been terminated without achieving their objectives. Within this context, the German Federal Ministry of Education and Research (BMBF) made a careful analysis of all national and international research projects conducted in the field of speech and language technology before deciding to launch an eight-year basic-research lead project in which research groups were to cooperate in an interdisciplinary and international effort covering the disciplines of computer science, computational linguistics, translation science, signal processing, communi cation science and artificial intelligence. At some point, the project comprised up to 135 work packages with up to 33 research groups working on these packages. The project was controlled by means of a network plan. Every two years the project sit uation was assessed and the project goals were updated. An international scientific advisory board provided advice for BMBF. A new scientific approach was chosen for this project: coping with the com plexity of spontaneous speech with all its pertinent phenomena such as ambiguities, self-corrections, hesitations and disfluencies took precedence over the intended lex icon size. Another important aspect was that prosodic information was exploited at all processing stages.

Recent Advances in Example-Based Machine Translation is of relevance to researchers and program developers in the field of Machine Translation and especially Example-Based Machine Translation, bilingual text processing and cross-linguistic information retrieval. It is also of interest to translation technologists and localisation professionals. Recent Advances in Example-Based Machine Translation fills a void, because it is the first book to tackle the issue of EBMT in depth. It gives a state-of-the-art overview of EBMT techniques and provides a coherent structure in which all aspects of EBMT are embedded. Its contributions are written by long-standing researchers in the field of MT in general, and EBMT in particular. This book can be used in graduate-level courses in machine translation and statistical NLP.

These proceedings gather contributions presented at the 3rd International Conference of Mechatronics and Cyber-MixMechatronics/ICOMECYME, organized by the National Institute of R&D in Mechatronics and Measurement Technique in Bucharest, Romania, on September 5th–6th, 2019. Reflecting the expansion mechatronics, it discusses topics in the newer trans-disciplinary fields, such as adaptronics, integronics, and cyber-mixmechatronics. With a rich scientific tradition and attracting specialists from around the globe – including North America, South America, and Asia – ICOMECYME focuses on presenting the latest research. It is mainly directed at academics and advanced students, but also appeals to R&D experts, offering a platform for scientific exchange. These proceedings are a valuable resource for entrepreneurs who want to invest in research and who are open for collaborations.

Human language capabilities are based on mental proceduresthat are closely linked to the time domain. Listening, understanding,and reacting, on the one hand, as well as planning,formulating,and speaking,onthe other, are performedin a highlyover lapping manner, thus allowing inter human communication to proceed in a smooth and ?uent way. Although it happens to be the natural mode of human language interaction, in cremental processing is still far from becoming a common feature of today’s lan guage technology. Instead, it will certainly remain one of the big challenges for research activities in the years to come. Usually considered dif?cult to a degree that rendersit almost intractableforpracticalpurposes,incrementallanguageprocessing has recently been attracting a steadily growing interest in the spoken language pro cessing community. Its notorious dif?culty can be attributed mainly to two reasons: Due to the inaccessibility of the right context, global optimization criteria are no longer available. This loss must be compensated for by communicating larger search spaces between system components or by introducing appropriate repair mechanisms. In any case, the complexity of the task can easily grow by an order of magnitude or even more. Incrementality is an almost useless feature as long as it remains a local property of individual system components. The advantages of incremental processing can be effectiveonly if all the componentsof a producer consumerchain consistently adhere to the same pattern of temporal behavior.