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In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here. The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent. The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.
Speech recognition technology is being increasingly employed in human-machine interfaces. A remaining problem however is the robustness of this technology to non-native accents, which still cause considerable difficulties for current systems. In this book, methods to overcome this problem are described. A speaker adaptation algorithm that is capable of adapting to the current speaker with just a few words of speaker-specific data based on the MLLR principle is developed and combined with confidence measures that focus on phone durations as well as on acoustic features. Furthermore, a specific pronunciation modelling technique that allows the automatic derivation of non-native pronunciations without using non-native data is described and combined with the previous techniques to produce a robust adaptation to non-native accents in an automatic speech recognition system.
Technology-Enhanced Language Learning for Specialized Domains provides an exploration of the latest developments in technology-enhanced learning and the processing of languages for specific purposes. It combines theoretical and applied research from an interdisciplinary angle, covering general issues related to learning languages with computers, assessment, mobile-assisted language learning, the new language massive open online courses, corpus-based research and computer-assisted aspects of translation. The chapters in this collection include contributions from a number of international experts in the field with a wide range of experience in the use of technologies to enhance the language learning process. The essays have been brought together precisely in recognition of the demand for this kind of specialised tuition, offering state-of-the-art technological and methodological innovation and practical applications. The topics covered revolve around the practical consequences of the current possibilites of mobility for both learners and teachers, as well as the applicability of updated technological advances to language learning and teaching, particularly in specialized domains. This is achieved through the description and discussion of practical examples of those applications in a variety of educational contexts. At the beginning of each thematic section, readers will find an introductory chapter which contextualises the topic and links the different examples discussed. Drawing together rich primary research and empirical studies related to specialized tuition and the processing of languages, Technology-Enhanced Language Learning for Specialized Domains will be an invaluable resource for academics, researchers and postgraduate students in the fields of education, computer assisted language learning, languages and linguistics, and language teaching.
These proceedings presents the state-of-the-art in spoken dialog systems with applications in robotics, knowledge access and communication. It addresses specifically: 1. Dialog for interacting with smartphones; 2. Dialog for Open Domain knowledge access; 3. Dialog for robot interaction; 4. Mediated dialog (including crosslingual dialog involving Speech Translation); and,5. Dialog quality evaluation. These articles were presented at the IWSDS 2012 workshop.
This book constitutes the refereed proceedings of the Third International Conference on Statistical Language and Speech Processing, SLSP 2015, held in Budapest, Hungary, in November 2015. The 26 full papers presented together with two invited talks were carefully reviewed and selected from 71 submissions. The papers cover topics such as: anaphora and coreference resolution; authorship identification, plagiarism and spam filtering; computer-aided translation; corpora and language resources; data mining and semantic Web; information extraction; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural language understanding; neural representation of speech and language; opinion mining and sentiment analysis; parsing; part-of-speech tagging; question-answering systems; semantic role labelling; speaker identification and verification; speech and language generation; speech recognition; speech synthesis; speech transcription; spelling correction; spoken dialogue systems; term extraction; text categorisation; text summarisation; and user modeling.
In the last decade, further applications of speech processing were developed, such as speaker recognition, human-machine interaction, non-English speech recognition, and non-native English speech recognition. This book addresses a few of these applications. Furthermore, major challenges that were typically ignored in previous speech recognition research, such as noise and reverberation, appear repeatedly in recent papers. I would like to sincerely thank the contributing authors, for their effort to bring their insights and perspectives on current open questions in speech recognition research.
This book highlights selected papers from the Mechanical Engineering track, with a focus on mechatronics and manufacturing, presented at the “Malaysian Technical Universities Conference on Engineering and Technology” (MUCET 2019). The conference brings together researchers and professionals in the fields of engineering, research and technology, providing a platform for future collaborations and the exchange of ideas.
This book highlights recent research on intelligent systems and nature-inspired computing. It presents 223 selected papers from the 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022), which was held online. The ISDA is a premier conference in the field of computational intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry. Including contributions by authors from 65 countries, the book offers a valuable reference guide for all researchers, students, and practitioners in the fields of computer science and engineering.
This book focuses on recent and emerging techniques for the enhancement of smart healthcare, smart communication, and smart transportation systems. It covers topics ranging from Machine Learning techniques, the Internet of Things (IoT), security aspects of medical documents, the performance of various protocols used in the communication and transportation environment, simulation of systems for real-time applications, and overall analysis of the previously mentioned. Applications such as transportation systems, stock market prediction, Smart Cities, and vehicular communication are dealt with. Features: Covers three important aspects of smart cities i.e., healthcare, smart communication and information, and smart transportation technologies. Discusses various security aspects of medical documents and the data preserving mechanisms. Provides better solutions using IoT techniques for healthcare, transportation, and communication systems. Includes the implementation example, various datasets, experimental results, and simulation procedures. Offers solutions for various disease prediction systems with intelligent techniques. This book is aimed at researchers and graduate students in computer science, electrical engineering, and data analytics.