10,110 research outputs found
PHONOTACTIC AND ACOUSTIC LANGUAGE RECOGNITION
Práce pojednává o fonotaktickĂ©m a akustickĂ©m pĹ™Ăstupu pro automatickĂ© rozpoznávánĂ jazyka. Prvnà část práce pojednává o fonotaktickĂ©m pĹ™Ăstupu zaloĹľenĂ©m na vĂ˝skytu fonĂ©movĂ˝ch sekvenci v Ĺ™eÄŤi. NejdĹ™Ăve je prezentován popis vĂ˝voje fonĂ©movĂ©ho rozpoznávaÄŤe jako techniky pro pĹ™epis Ĺ™eÄŤi do sekvence smysluplnĂ˝ch symbolĹŻ. HlavnĂ dĹŻraz je kladen na dobrĂ© natrĂ©novánĂ fonĂ©movĂ©ho rozpoznávaÄŤe a kombinaci vĂ˝sledkĹŻ z nÄ›kolika fonĂ©movĂ˝ch rozpoznávaÄŤĹŻ trĂ©novanĂ˝ch na rĹŻznĂ˝ch jazycĂch (ParalelnĂ fonĂ©movĂ© rozpoznávánĂ následovanĂ© jazykovĂ˝mi modely (PPRLM)). Práce takĂ© pojednává o novĂ© technice anti-modely v PPRLM a studuje pouĹľitĂ fonĂ©movĂ˝ch grafĹŻ mĂsto nejlepšĂho pĹ™episu. Na závÄ›r práce jsou porovnány dva pĹ™Ăstupy modelovánĂ vĂ˝stupu fonĂ©movĂ©ho rozpoznávaÄŤe -- standardnĂ n-gramovĂ© jazykovĂ© modely a binárnĂ rozhodovacĂ stromy. HlavnĂ pĹ™Ănos v akustickĂ©m pĹ™Ăstupu je diskriminativnĂ modelovánĂ cĂlovĂ˝ch modelĹŻ jazykĹŻ a prvnĂ experimenty s kombinacĂ diskriminativnĂho trĂ©novánĂ a na pĹ™ĂznacĂch, kde byl odstranÄ›n vliv kanálu. Práce dále zkoumá rĹŻznĂ© druhy technik fĂşzi akustickĂ©ho a fonotaktickĂ©ho pĹ™Ăstupu. Všechny experimenty jsou provedeny na standardnĂch datech z NIST evaluaci konanĂ© v letech 2003, 2005 a 2007, takĹľe jsou pĹ™Ămo porovnatelnĂ© s vĂ˝sledky ostatnĂch skupin zabĂ˝vajĂcĂch se automatickĂ˝m rozpoznávánĂm jazyka. S fĂşzĂ uvedenĂ˝ch technik jsme posunuli state-of-the-art vĂ˝sledky a dosáhli vynikajĂcĂch vĂ˝sledkĹŻ ve dvou NIST evaluacĂch.This thesis deals with phonotactic and acoustic techniques for automatic language recognition (LRE). The first part of the thesis deals with the phonotactic language recognition based on co-occurrences of phone sequences in speech. A thorough study of phone recognition as tokenization technique for LRE is done, with focus on the amounts of training data for phone recognizer and on the combination of phone recognizers trained on several language (Parallel Phone Recognition followed by Language Model - PPRLM). The thesis also deals with novel technique of anti-models in PPRLM and investigates into using phone lattices instead of strings. The work on phonotactic approach is concluded by a comparison of classical n-gram modeling techniques and binary decision trees. The acoustic LRE was addressed too, with the main focus on discriminative techniques for training target language acoustic models and on initial (but successful) experiments with removing channel dependencies. We have also investigated into the fusion of phonotactic and acoustic approaches. All experiments were performed on standard data from NIST 2003, 2005 and 2007 evaluations so that the results are directly comparable to other laboratories in the LRE community. With the above mentioned techniques, the fused systems defined the state-of-the-art in the LRE field and reached excellent results in NIST evaluations.
Perspectives of Nuclear Physics in Europe: NuPECC Long Range Plan 2010
The goal of this European Science Foundation Forward Look into the future of Nuclear Physics is to bring together
the entire Nuclear Physics community in Europe to formulate a coherent plan of the best way to develop the field in
the coming decade and beyond.<p></p>
The primary aim of Nuclear Physics is to understand the origin, evolution, structure and phases of strongly interacting matter, which constitutes nearly 100% of the visible matter in the universe. This is an immensely important and challenging task that requires the concerted effort of scientists working in both theory and experiment, funding agencies, politicians and the public.<p></p>
Nuclear Physics projects are often “big science”, which implies large investments and long lead times. They need careful forward planning and strong support from policy makers. This Forward Look provides an excellent tool to achieve this. It represents the outcome of detailed scrutiny by Europe’s leading experts and will help focus the views of the scientific community on the most promising directions in the field and create the basis for funding agencies to provide adequate support.<p></p>
The current NuPECC Long Range Plan 2010 “Perspectives of Nuclear Physics in Europe” resulted from consultation
with close to 6 000 scientists and engineers over a period of approximately one year. Its detailed recommendations
are presented on the following pages. For the interested public, a short summary brochure has been produced to
accompany the Forward Look.<p></p>
A detection-based pattern recognition framework and its applications
The objective of this dissertation is to present a detection-based pattern recognition framework and demonstrate its applications in automatic speech recognition and broadcast news video story segmentation.
Inspired by the studies of modern cognitive psychology and real-world pattern recognition systems, a detection-based pattern recognition framework is proposed to provide an alternative solution for some complicated pattern recognition problems. The primitive features are first detected and the task-specific knowledge hierarchy is constructed level by level; then a variety of heterogeneous information sources are combined together and the high-level context is incorporated as additional information at certain stages.
A detection-based framework is a â divide-and-conquerâ design paradigm for pattern recognition problems, which will decompose a conceptually difficult problem into many elementary sub-problems that can be handled directly and reliably. Some information fusion strategies will be employed to integrate the evidence from a lower level to form the evidence at a higher level. Such a fusion procedure continues until reaching the top level. Generally, a detection-based framework has many advantages: (1) more flexibility in both detector design and fusion strategies, as these two parts
can be optimized separately; (2) parallel and distributed computational components in primitive feature detection. In such a component-based framework, any primitive component can be replaced by a new one while other components remain unchanged; (3) incremental information integration; (4) high level context information as additional information sources, which can be combined with bottom-up processing at any stage.
This dissertation presents the basic principles, criteria, and techniques for detector design and hypothesis verification based on the statistical detection and decision theory. In addition, evidence fusion strategies were investigated in this dissertation. Several novel detection algorithms and evidence fusion methods were proposed and their effectiveness was justified in automatic speech recognition and broadcast news video segmentation system. We believe such a detection-based framework can be employed
in more applications in the future.Ph.D.Committee Chair: Lee, Chin-Hui; Committee Member: Clements, Mark; Committee Member: Ghovanloo, Maysam; Committee Member: Romberg, Justin; Committee Member: Yuan, Min
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