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Automatic Speech and Speaker Recognition
Research in the field of automatic speech and speaker recognition has made a number of significant advances in the last two decades, influenced by advances in signal processing, algorithms, architectures, and hardware. These advances include: the adoption of a statistical pattern recognition paradigm; the use of the hidden Markov modeling framework to characterize both the spectral and the temporal variations in the speech signal; the use of a large set of speech utterance examples from a large population of speakers to train the hidden Markov models of some fundamental speech units; the organization of speech and language knowledge sources into a structural finite state network; and the use...
Innovation Together
Since its establishment in 1998, Microsoft Research Asia’s trademark and long term commitment has been to foster innovative research and advanced education in the Asia-Pacific region. Through open collaboration and partnership with universities, government and other academic partners, MSRA has been consistently advancing the state-of-the-art in computer science. This book was compiled to record these outstanding collaborations, as Microsoft Research Asia celebrates its 10th Anniversary. The selected papers are all authored or co-authored by faculty members or students through collaboration with MSRA lab researchers, or with the financial support of MSRA. Papers previously published in top-tier international conference proceedings and journals are compiled here into one accessible volume of outstanding research. Innovation Together highlights the outstanding work of Microsoft Research Asia as it celebrates ten years of achievement and looks forward to the next decade of success.
STACS 97
This book constitutes the refereed proceedings of the 14th Annual Symposium on Theoretical Aspects of Computer Science, STACS 97, held in Lübeck, Germany, in February/March 1997. The 46 revised full papers included were carefully selected from a total of 139 submissions; also included are three invited full papers. The papers presented span the whole scope of theoretical computer science. Among the topics covered are, in particular, algorithms and data structures, computational complexity, automata and formal languages, structural complexity, parallel and distributed systems, parallel algorithms, semantics, specification and verification, logic, computational geometry, cryptography, learning and inductive inference.
European Language Equality
This open access book presents a comprehensive collection of the European Language Equality (ELE) project’s results, its strategic agenda and roadmap with key recommendations to the European Union on how to achieve digital language equality in Europe by 2030. The fabric of the EU linguistic landscape comprises 24 official languages and over 60 regional and minority languages. However, language barriers still hamper communication and the free flow of information. Multilingualism is a key cultural cornerstone of Europe, signifying what it means to be and to feel European. Various studies and resolutions have found a striking imbalance in the support of Europe’s languages through technologi...
The Oxford Handbook of Computational Linguistics
Ruslan Mitkov's highly successful Oxford Handbook of Computational Linguistics has been substantially revised and expanded in this second edition. Alongside updated accounts of the topics covered in the first edition, it includes 17 new chapters on subjects such as semantic role-labelling, text-to-speech synthesis, translation technology, opinion mining and sentiment analysis, and the application of Natural Language Processing in educational and biomedical contexts, among many others. The volume is divided into four parts that examine, respectively: the linguistic fundamentals of computational linguistics; the methods and resources used, such as statistical modelling, machine learning, and corpus annotation; key language processing tasks including text segmentation, anaphora resolution, and speech recognition; and the major applications of Natural Language Processing, from machine translation to author profiling. The book will be an essential reference for researchers and students in computational linguistics and Natural Language Processing, as well as those working in related industries.
Speech Prosody in Speech Synthesis: Modeling and generation of prosody for high quality and flexible speech synthesis
The volume addresses issues concerning prosody generation in speech synthesis, including prosody modeling, how we can convey para- and non-linguistic information in speech synthesis, and prosody control in speech synthesis (including prosody conversions). A high level of quality has already been achieved in speech synthesis by using selection-based methods with segments of human speech. Although the method enables synthetic speech with various voice qualities and speaking styles, it requires large speech corpora with targeted quality and style. Accordingly, speech conversion techniques are now of growing interest among researchers. HMM/GMM-based methods are widely used, but entail several major problems when viewed from the prosody perspective; prosodic features cover a wider time span than segmental features and their frame-by-frame processing is not always appropriate. The book offers a good overview of state-of-the-art studies on prosody in speech synthesis.
Theory and Novel Applications of Machine Learning
Even since computers were invented, many researchers have been trying to understand how human beings learn and many interesting paradigms and approaches towards emulating human learning abilities have been proposed. The ability of learning is one of the central features of human intelligence, which makes it an important ingredient in both traditional Artificial Intelligence (AI) and emerging Cognitive Science. Machine Learning (ML) draws upon ideas from a diverse set of disciplines, including AI, Probability and Statistics, Computational Complexity, Information Theory, Psychology and Neurobiology, Control Theory and Philosophy. ML involves broad topics including Fuzzy Logic, Neural Networks (NNs), Evolutionary Algorithms (EAs), Probability and Statistics, Decision Trees, etc. Real-world applications of ML are widespread such as Pattern Recognition, Data Mining, Gaming, Bio-science, Telecommunications, Control and Robotics applications. This books reports the latest developments and futuristic trends in ML.
