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1
Wagenmakers, Eric-Jan. "Priming in visual word recognition empirical studies and computational models /". [S.l. : Amsterdam : s.n.] ; Universiteit van Amsterdam [Host], 2001. http://dare.uva.nl/document/85533.
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Lacouture, Yves. "Connectionist models of choice and reaction time in psychophysics and word recognition". Thesis, McGill University, 1990. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=74588.
Testo completoAbstract (sommario):
A connectionist architecture is developed that can be used for modeling choice probabilities and reaction times in psychophysics and word recognition. The network architecture consists of a feed-forward network and a decoding module. Learning is by mean-variance back-propagation, an extension of the standard back-propagation learning algorithm. The new learning procedure is interpreted as a selective attention mechanism, and leads to a better model of learning in simple identification tasks than the standard back-propagation. Choice probabilities are modeled by the input/output relations of the network, and reaction times are modeled by the time taken for the network, particularly the decoding module, to achieve a stable state. The model is applied to both unidimensional and multidimensional identification tasks in psychophysics and to word recognition.
3
Engbrecht, Jeffery W. "Word hypothesis of phonetic strings using hidden Markov models /". Online version of thesis, 1990. http://hdl.handle.net/1850/10604.
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Taylor, John Powell. "Recognition of words post-assimilation contrasting two models of speech perception /". abstract and full text PDF (free order & download UNR users only), 2005. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1433278.
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Kurcan, Remzi Serdar. "Isolated word recognition from in-ear microphone data using Hidden Markov Models (HMM)". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Mar%5FKurcan.pdf.
Testo completoAbstract (sommario):
Thesis (M.S. in Electrical Engineering and M.S. in Systems Engineering)--Naval Postgraduate School, March 2006.Thesis Advisor(s): Monique P. Fargues, David Jenn. "March 2006." Includes bibliographical references (p.147-151). Also available online.
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Humphreys, Jane. "WIRDS, WERDS, WYRDZ : visual wordlikeness, lexical phonology, and models of visual word recognition". Thesis, University of Bristol, 2008. http://hdl.handle.net/1983/7f7f66b6-f4e7-420e-ab74-af32bbec6ce0.
Testo completoAbstract (sommario):
Nonwords such as 'brate' and pseudohomophones such as 'brane' are often used to explore the processes involved in decoding orthography, without the potential confound from semantics. Experiments using these usefuJ.items can provide evidence that sheds light on competing models ofvisual word recognition in general and the status oflexical phonology in particular. However, previous experiments have often used stimuli that look implausible as exemplars ofEnglish spelling, (e.g. phret, woez), and it is arguable that some ofthe current controversies in the area may be partly attributable to the use ofsuch stimuli. To investigate this notion, new items were constructed from real words on the grounds that they would contain a high proportion ofexisting orthotactic patterns. Ratings were gathered for the visual wordlikeness ofthe previous stimuli and these new items; the latter generated higher ratings than the former. Analysis ofthe ratings suggested that readers are sensitive to multiple sources oforthographic and graphophonemic information. In a series of naming and lexical decision experiments using the new stimuli, results showed that participants responded to visual wordlikeness across all tasks; for example, reading wordlike pseudohomophones more quickly than unwordlike, and responding to them more slowly in visual lexical decision. A masked priming experiment using wordlike and unwordlike primes showed that lexical phonology was less likely to be activated for the unwordlike pseudohomophones than the wordlike. Overall, the results support a view ofvisual word recognition as a highly-interactive system, processing multiple grain-sizes ofsuhlexical and lexical information in which phonology plays a functional, non-optional, role. While orthotactic violations constrain its normal workings, the system has mechanisms that can be used to process unwordlike items; but it is unlikely that these processes are the same in all respects as those used for wordlike stimuli.
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McMillan, David Evans. "Time-varying linear prediction as a base for an isolated-word recognition algorithm". Thesis, Virginia Tech, 1987. http://hdl.handle.net/10919/45777.
Testo completoAbstract (sommario):
There is a vast amount of research being done in the area of voice recognition. A large portion of this research concentrates on developing algorithms that will yield higher accuracy rates; such as algorithms based on dynamic time warping, vector quantization, and other mathematical methods [l2][21][l5].
In this research, the evaluation of the feasibility of using linear prediction (LP) with time-varying parameters as a base for a voice recognition algorithm will be investigated. First the development of an anti-aliasing filter is discussed with some results from the filter hardware realization included. Then a brief discussion of LP is presented and a method for time-varying LP is derived from this discussion. A comparison between time-varying and segmentation LP is made and a description of the developed algorithm that tests time-varying LP as a recognition technique is given. The evaluation is conducted with the developed algorithm configured for speaker-dependent and speaker-independent isolated-word recognition.
The conclusion drawn from this research is that this particular technique of voice recognition is very feasible as a base for a voice recognition algorithm. With the incorporation of other techniques, a complete algorithm can conceivably be developed that will yield very high accuracy rates. Recommendations for algorithm improvements are given along with other techniques that might be added to make a complete recognition algorithm.Master of Science
8
Wang, Wenwei [Verfasser]. "Off-line Cursive Handwritten Word Recognition Using Hidden Markov Models and Multiple Classifier Combination / Wenwei Wang". Aachen : Shaker, 2003. http://d-nb.info/1174514469/34.
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Prum, Sophea. "On the use of a discriminant approach for handwritten word recognition based on bi-character models". Thesis, La Rochelle, 2013. http://www.theses.fr/2013LAROS418/document.
Testo completoAbstract (sommario):
Avec l’avènement des dispositifs nomades tels que les smartphones et les tablettes, la reconnaissance automatique de l’écriture manuscrite cursive à partir d’un signal en ligne est devenue durant les dernières décennies un besoin réel de la vie quotidienne à l’ère numérique. Dans le cadre de cette thèse, nous proposons de nouvelles stratégies pour un système de reconnaissance de mots manuscrits en-ligne. Ce système se base sur une méthode collaborative segmentation/reconnaissance et en utilisant des analyses à deux niveaux : caractère et bi-caractères. Plus précisément, notre système repose sur une segmentation de mots manuscrits en graphèmes afin de créer un treillis à L niveaux. Chaque noeud de ce treillis est considéré comme un caractère potentiel envoyé à un moteur de Reconnaissance de Caractères Isolés (RCI) basé sur un SVM. Pour chaque noeud, ce dernier renvoie une liste de caractères associés à une liste d’estimations de probabilités de reconnaissance. Du fait de la grande diversité des informations résultant de la segmentation en graphèmes, en particulier à cause de la présence de morceaux de caractères et de ligatures, l’injection de chacun des noeuds du treillis dans le RCI engendre de potentielles ambiguïtés au niveau du caractère. Nous proposons de lever ces ambiguïtés en utilisant des modèles de bi-caractères, basés sur une régression logistique dont l’objectif est de vérifier la cohérence des informations à un niveau de reconnaissance plus élevé. Finalement, les résultats renvoyés par le RCI et l’analyse des modèles de bi-caractères sont utilisés dans la phase de décodage pour parcourir le treillis dans le but de trouver le chemin optimal associé à chaque mot dans le lexique. Deux méthodes de décodage sont proposées (recherche heuristique et programmation dynamique), la plus efficace étant basée sur de la programmation dynamiqueWith the advent of mobile devices such as tablets and smartphones over the last decades, on-line handwriting recognition has become a very highly demanded service for daily life activities and professional applications. This thesis presents a new approach for on-line handwriting recognition. This approach is based on explicit segmentation/recognition integrated in a two level analysis system: character and bi-character. More specifically, our system segments a handwritten word in a sequence of graphemes to be then used to create a L-levels lattice of graphemes. Each node of the lattice is considered as a character to be submitted to a SVM based Isolated Character Recognizer (ICR). The ICR returns a list of potential character candidates, each of which is associated with an estimated recognition probability. However, each node of the lattice is a combination of various segmented graphemes. As a consequence, a node may contain some ambiguous information that cannot be handled by the ICR at character level analysis. We propose to solve this problem using "bi-character" models based on Logistic Regression, in order to verify the consistency of the information at a higher level of analysis. Finally, the recognition results provided by the ICR and the bi-character models are used in the word decoding stage, whose role is to find the optimal path in the lattice associated to each word in the lexicon. Two methods are presented for word decoding (heuristic search and dynamic programming), and dynamic programming is found to be the most effective
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Nimmo, Lisa M. "Investigating the phonological similarity effect implications for short-term memory models /". Access electronically, 2004. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20041105.101632/index.html.
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Rytting, Christopher Anton. "Preserving subsegmental variation in modeling word segmentation (or, the raising of baby Mondegreen)". Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1167698589.
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Chapman, Allison M. "List length and word frequency effects in the Sternberg paradigm". The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1337818585.
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Vodička, Radek. "Rozpoznávání izolovaných slov". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220658.
Testo completoAbstract (sommario):
Main purpose of the thesis is to study the processes and methods of isolated words recognition. In the theoretical part a basic principals are explained. The practical part is about the program creating using these principles in practice. For isolated words recognition Hidden Markov Models (HMM) are used, for obtaining decision symptoms cepstral analysis is chosen.
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Goff, Deborah, e debannegoff@yahoo co uk. "The relationship between children's reading comprehension, word reading, language skills and memory in a normal sample". La Trobe University. School of Psychological Science, 2004. http://www.lib.latrobe.edu.au./thesis/public/adt-LTU20060626.103641.
Testo completoAbstract (sommario):
The current study aimed to develop a model of reading comprehension for children in middle primary school. As part of this overall aim there was a particular focus on the contribution of different types of memory to reading comprehension. The variables selected for consideration were identified from the child and adult literature and were of three types: word reading, language, and memory. The sample comprised 180 primary school children in grades 3-5 recruited from two primary schools. Their ages ranged from 8 years 7 months to 11 years 11 months. The reading comprehension measure was in a multiple-choice format with the text available when answering the questions. The five word reading measures were phonological recoding, orthographic processing, text reading accuracy, text reading speed, and a measure of exposure to print and reading experience. It is recognised that, although exposure to print is closely associated with word reading skills, it is not a direct measure of word reading. The language measures were oral comprehension, receptive vocabulary and receptive grammatical skills. The memory measures included measures of verbal and visuospatial short-term memory, measures of verbal and visuospatial working memory, a measure of the ability to inhibit irrelevant information from working memory and a measure of longer term verbal learning and retrieval. Correlational and hierachical multiple regression analyses were used to extrapolate the relationships between and among these variables.
The results revealed that, after controlling for age and general intellectual ability, the word reading and the language variables had a much stronger relationship with reading comprehension than the memory variables. The strongest independent predictors of reading comprehension were orthographic processing and oral comprehension. An additive combination of these two variables provided a more parsimonious model of reading comprehension than other models under consideration. It was concluded that for the age range in this study, language and word reading skills are the main predictors of reading comprehension and that the different types of memory do not make major contributions to reading comprehension.
15
Nobre, Alexandre de Pontes. "Processamento léxico-semântico : relações com reconhecimento visual de palavras e compreensão de leitura textual". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2013. http://hdl.handle.net/10183/101860.
Testo completoAbstract (sommario):
Esta dissertação teve como objetivo investigar as relações entre reconhecimento de palavras e compreensão de leitura textual e o processamento léxico. A dissertação é constituída de dois estudos. No primeiro estudo, são revisados modelos de leitura de palavras e de texto com o objetivo de examinar o papel do processamento léxico-semântico no reconhecimento visual de palavras e na compreensão de leitura textual. O paradigma de priming semântico é apresentado como uma ferramenta para a investigação da relação entre processamento léxico-semântico e ambos os componentes de leitura examinados. São apresentados os principais modelos teóricos de priming semântico, juntamente com uma revisão dos estudos empíricos que relacionam priming semântico e leitura, e algumas conclusões e perspectivas de investigação são apresentadas. No segundo estudo, foram investigadas empiricamente as relações entre processamento léxico-semântico e leitura (reconhecimento visual de palavras e compreensão de leitura textual) em uma amostra de 68 crianças, de 7 a 12 anos, de escolas particulares de Porto Alegre. O processamento léxico-semântico foi avaliado através de uma tarefa de decisão lexical no paradigma de priming semântico, enquanto as habilidades de leitura foram medidas por uma tarefa de leitura de palavras/pseudopalavras isoladas e uma tarefa de compreensão de leitura textual (resposta a questões e reconto de história). Foram investigadas correlações entre efeitos de priming semântico e desempenho em tarefas de leitura de palavras e compreensão de leitura textual e se o priming semântico prediz o desempenho dos participantes nas tarefas de leitura. Os resultados mostraram que o priming semântico se correlaciona com ambas as medidas de leitura, e que o reconhecimento de palavras medeia parcialmente a relação entre processamento léxico-semântico e compreensão de leitura textual.The aim of this dissertation was to investigate the relationships between word recognition and reading comprehension with lexical-semantic processing. The dissertation is composed of two studies. In the first study, models of word reading and reading comprehension are reviewed in order to examine the role of lexical-semantic processing in visual word recognition and in reading comprehension. The semantic priming paradigm is presented as an instrument for the investigation of relationships between lexical-semantic processing and the components of reading examined. The main theoretical models of semantic priming are presented and a review of studies which relate semantic priming and reading is conducted, and some conclusions and perspectives for investigation are presented. In the second study, relations between lexical-semantic processing and reading (visual word recognition and reading comprehension) were investigated empirically in a sample of 68 children, aged seven to twelve years, from private schools in Porto Alegre, Brazil. Lexical-semantic processing was evaluated by a lexical decision task in the semantic priming paradigm and reading abilities were assessed with a word/nonword reading task and a reading comprehension task (questionnaire and story retelling). Correlations between semantic priming effects and word reading and reading comprehension were investigated, as well as if semantic priming effects predict performance on the reading task. Results showed that semantic priming correlates with both groups of reading measures, and that word reading partially mediates the relation between lexical-semantic processing and reading comprehension.
16
Seybold, John. "An attractor neural network model of spoken word recognition". Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335839.
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Zheng, Zhonghua. "Chinese characters and word recognition: An analysis and a model". Thesis, University of Ottawa (Canada), 1990. http://hdl.handle.net/10393/5573.
Testo completoAbstract (sommario):
Designations have been used very inconsistently in deciphering the nature of the Chinese writing system, ranging from pictographic, ideographic, logographic, to morphemic, phonosemantic, ideophonographic, and even to logosyllabic, word syllabic, morphosyllabic, etc. Implicit in the inconsistence is a set of hypotheses that Chinese is not a phonetic script, Chinese characters are represented in the right hemisphere and thus are processed in a picture-like fashion, and that recognizing Chinese characters does not involve phonological mediation, and so on. This thesis provides a thorough discussion of the linguistic structure underlying the organization of Chinese characters, and offers a perspective on the linguistic organization and the psycholinguistic processes involved in the recognition of Chinese characters. Misconceptions and fallacies concerning Chinese characters in both linguistic and cognitive areas are challenged and clarified. The thesis begins with a linguistic analysis of Chinese characters, focussing on the formal properties around which processing interpretations revolve. It then discusses issues of visual, hemispheric and cognitive processing of Chinese characters (e.g., how a Chinese character is visually detected? are Chinese characters represented in the right hemisphere? how are they processed in the two hemispheres? under what circumstances are Chinese characters visually accessed? and through what means if a Chinese character is to be phonologically coded? etc.). Lastly, an interactive model of Chinese character recognition is proposed. It is hoped that the groundwork may serve as the basis for proper experimental psycholinguistic research in future.
18
Xu, Lei. "Phonological variation and word recognition in continuous speech". Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1190048116.
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Harrison, Bush Aryn Lyn. "Effects of Mild Cognitive Impairment on Visual Word Recognition: A Longitudinal Investigation". University of Akron / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=akron1144771075.
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Kedwell, Mary. "A 2-phase model of word encoding and a trial of its associated intervention /". [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18962.pdf.
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Jankowski, Scott Steven. "The influence of task demands on familiarity effects in visual word recognition a cohort model perspective /". Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1148583565.
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George, Dileep. "How the brain might work : a hierarchical and temporal model for learning and recognition /". May be available electronically:, 2008. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.
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23
Wu, Hongmei. "Mechanisms of Masked Priming: Testing the Entry Opening Model". Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/228453.
Testo completoAbstract (sommario):
Since it was introduced in Forster and Davis (1984), masked priming has been widely adopted in the psycholinguistic research on visual word recognition, but there has been little consensus on its actual mechanisms, i.e. how it occurs and how it should be interpreted. This dissertation addresses two different interpretations of masked priming, one based on the Interactive Activation Model (McClelland & Rumelhart, 1981), in which priming is seen as a result of persisting activation from the prime, the other based on the Entry Opening Model (Forster & Davis, 1984), which sees priming as a savings effect. Five experiments are reported testing contrasting hypotheses about the role of prime duration and prime-target asynchrony (SOA) in masked priming using both identity and form priming. Overall, this dissertation lends support to the Entry Opening Model, demonstrating that masked priming is essentially a savings effect, and that as such, it is determined by the SOA, not the prime duration per se.
24
Kim, Woojae. "Understanding the connectionist modeling of quasiregular mappings in reading aloud". Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1171994549.
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Braubartas, Ernestas. "Lietuvių kalbos atpažinimas, panaudojant Julius programinę įrangą". Master's thesis, Lithuanian Academic Libraries Network (LABT), 2008. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20080929_112655-51844.
Testo completoAbstract (sommario):
Signalų technologijų magistro darbo tema yra aktuali, nes nebepakanka įprastų informacijos įvedimo priemonių. Todėl ieškoti ir apdoroti informaciją, valdyti sudėtingus įrenginius ir programas daug patogiau būtų jei kompiuteriai ir įvairūs įrenginiai suprastų žmogaus kalbą. Pasaulyje panašios sistemos kuriamos jau daugelį metų. Tačiau šiuo metu lietuvių kalbos atpažinimo sistemos yra dar tik kūrimo stadijoje. Darbe nagrinėjamas Lietuvių kalbos žodžių atpažinimas skirstant juos į kategorijas ir naudojant paslėptuosius markovo modelius. Šio tyrimo tikslas – ištirti lietuvių kalbos žodžių skirstymo į kategorijas įtaką atpažinimo tikslumui.Taip pat tiriamas žodžių grupių bei pavienių žodžių atpažinimas. Akustinis modelis sukurtas su HTK paketu, kuris naudojasi paslėptųjų Markovo modelių metodika. Žodžių skirstymas į kategorijas aprašytas Backus-Naur formatu. Eksperimentai bus atliekami ir rezultatai gaunami naudojant, Julius programinės įrangos įrankius bei šio paketo, žodžių kategorijų pagrindu veikiančią, Julian kalbos atpažinimo sistemą. Geriausi rezultatai gauti bandant atpažinti pavienius žodžius suskirstytus į kategorijas. Atpažinimo tikslumas siekia 91 %. Bandant atpažinti žodžių sekas, nesuskirstytas į kategorijas, gautas atpažinimo tikslumas tesiekia 51 %. Microsoft Office Word 2003 meniu valdymo atpažinimo tikslumas siekia 82 %.The theme of Master project of signal technology is actual, because not enough usual information introduction ways. Therefore information search and processing, complicated devices and programs control would be more handily if computers and devices understood human speech. Similar systems are designing for many years in the world. However Lithuanian speech recognition systems are still developing in nowadays. The thesis treats of isolated Lithuanian words recognition dividing them into category and using Hidden Markov Models. The idea of research is to explore categorization of Lithuanian words influence on the accuracy of recognition. The recognition of single words and word groups is under research too. Acoustic model is constructed by using HTK toolkit which is based on Hidden Markov Models. Categorization of words is described with Backus-Naur form. Experiments are made with Julius software speech recognition system Julian witch performs words category based recognition. Best results are got trying to recognize single words set into categories. The accuracy rate of recognition reaches 91 %. While trying to recognize uncategorized word sequences – the accuracy rate of recognition reaches only 51 %. The accuracy rate of Microsoft Office Word 2003 control menu recognition reaches 82 %.
26
Hasasneh, Ahmad. "Robot semantic place recognition based on deep belief networks and a direct use of tiny images". Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00960289.
Testo completoAbstract (sommario):
Usually, human beings are able to quickly distinguish between different places, solely from their visual appearance. This is due to the fact that they can organize their space as composed of discrete units. These units, called ''semantic places'', are characterized by their spatial extend and their functional unity. Such a semantic category can thus be used as contextual information which fosters object detection and recognition. Recent works in semantic place recognition seek to endow the robot with similar capabilities. Contrary to classical localization and mapping works, this problem is usually addressed as a supervised learning problem. The question of semantic places recognition in robotics - the ability to recognize the semantic category of a place to which scene belongs to - is therefore a major requirement for the future of autonomous robotics. It is indeed required for an autonomous service robot to be able to recognize the environment in which it lives and to easily learn the organization of this environment in order to operate and interact successfully. To achieve that goal, different methods have been already proposed, some based on the identification of objects as a prerequisite to the recognition of the scenes, and some based on a direct description of the scene characteristics. If we make the hypothesis that objects are more easily recognized when the scene in which they appear is identified, the second approach seems more suitable. It is however strongly dependent on the nature of the image descriptors used, usually empirically derived from general considerations on image coding.Compared to these many proposals, another approach of image coding, based on a more theoretical point of view, has emerged the last few years. Energy-based models of feature extraction based on the principle of minimizing the energy of some function according to the quality of the reconstruction of the image has lead to the Restricted Boltzmann Machines (RBMs) able to code an image as the superposition of a limited number of features taken from a larger alphabet. It has also been shown that this process can be repeated in a deep architecture, leading to a sparse and efficient representation of the initial data in the feature space. A complex problem of classification in the input space is thus transformed into an easier one in the feature space. This approach has been successfully applied to the identification of tiny images from the 80 millions image database of the MIT. In the present work, we demonstrate that semantic place recognition can be achieved on the basis of tiny images instead of conventional Bag-of-Word (BoW) methods and on the use of Deep Belief Networks (DBNs) for image coding. We show that after appropriate coding a softmax regression in the projection space is sufficient to achieve promising classification results. To our knowledge, this approach has not yet been investigated for scene recognition in autonomous robotics. We compare our methods with the state-of-the-art algorithms using a standard database of robot localization. We study the influence of system parameters and compare different conditions on the same dataset. These experiments show that our proposed model, while being very simple, leads to state-of-the-art results on a semantic place recognition task.
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McEleney, Sarah Nicole. "La influencia del conocimiento de otras lenguas en la identificación de palabras en español L2: Un estudio de los modelos BIA y BIA+". Miami University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=miami1248105154.
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Kubalík, Jakub. "Mining of Textual Data from the Web for Speech Recognition". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237170.
Testo completoAbstract (sommario):
Prvotním cílem tohoto projektu bylo prostudovat problematiku jazykového modelování pro rozpoznávání řeči a techniky pro získávání textových dat z Webu. Text představuje základní techniky rozpoznávání řeči a detailněji popisuje jazykové modely založené na statistických metodách. Zvláště se práce zabývá kriterii pro vyhodnocení kvality jazykových modelů a systémů pro rozpoznávání řeči. Text dále popisuje modely a techniky dolování dat, zvláště vyhledávání informací. Dále jsou představeny problémy spojené se získávání dat z webu, a v kontrastu s tím je představen vyhledávač Google. Součástí projektu byl návrh a implementace systému pro získávání textu z webu, jehož detailnímu popisu je věnována náležitá pozornost. Nicméně, hlavním cílem práce bylo ověřit, zda data získaná z Webu mohou mít nějaký přínos pro rozpoznávání řeči. Popsané techniky se tak snaží najít optimální způsob, jak data získaná z Webu použít pro zlepšení ukázkových jazykových modelů, ale i modelů nasazených v reálných rozpoznávacích systémech.
29
Mihoubi, Douadi. "Modes de reconnaissance et équités dans les automates de mots infinis". Paris 13, 1989. http://www.theses.fr/1989PA132013.
Testo completoAbstract (sommario):
L'extension des grammaires linéaires et automates à pic aux ensembles de mots infinis est étudiée. Caractérisations de langages de mots infinis reconnus par des automates à pic. Etude des propriètés de fermeture de ces langages par les opérations booléennes et topologiques. Extension des concepts d'équités décrites sur: les systèmes de transitions finis, processus SCCS régulier et grammaires algébriques respectivement aux automates à pic, systèmes de N processus finis et à pic, et grammaires linéaires et bilinéaires
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Karaman, Svebor. "Indexation de la vidéo portée : application à l’étude épidémiologique des maladies liées à l’âge". Thesis, Bordeaux 1, 2011. http://www.theses.fr/2011BOR14402/document.
Testo completoAbstract (sommario):
Le travail de recherche de cette thèse de doctorat s'inscrit dans le cadre du suivi médical des patients atteints de démences liées à l'âge à l'aide des caméras videos portées par les patients. L'idée est de fournir aux médecins un nouvel outil pour le diagnostic précoce de démences liées à l'âge telles que la maladie d'Alzheimer. Plus précisément, les Activités Instrumentales du Quotidien (IADL: Instrumental Activities of Daily Living en anglais) doivent être indexées automatiquement dans les vidéos enregistrées par un dispositif d'enregistrement portable.Ces vidéos présentent des caractéristiques spécifiques comme de forts mouvements ou de forts changements de luminosité. De plus, la tâche de reconnaissance visée est d'un très haut niveau sémantique. Dans ce contexte difficile, la première étape d'analyse est la définition d'un équivalent à la notion de « plan » dans les contenus vidéos édités. Nous avons ainsi développé une méthode pour le partitionnement d'une vidéo tournée en continu en termes de « points de vue » à partir du mouvement apparent.Pour la reconnaissance des IADL, nous avons développé une solution selon le formalisme des Modèles de Markov Cachés (MMC). Un MMC hiérarchique à deux niveaux a été introduit, modélisant les activités sémantiques ou des états intermédiaires. Un ensemble complexe de descripteurs (dynamiques, statiques, de bas niveau et de niveau intermédiaire) a été exploité et les espaces de description joints optimaux ont été identifiés expérimentalement.Dans le cadre de descripteurs de niveau intermédiaire pour la reconnaissance d'activités nous nous sommes particulièrement intéressés aux objets sémantiques que la personne manipule dans le champ de la caméra. Nous avons proposé un nouveau concept pour la description d'objets ou d'images faisant usage des descripteurs locaux (SURF) et de la structure topologique sous-jacente de graphes locaux. Une approche imbriquée pour la construction des graphes où la même scène peut être décrite par plusieurs niveaux de graphes avec un nombre de nœuds croissant a été introduite. Nous construisons ces graphes par une triangulation de Delaunay sur des points SURF, préservant ainsi les bonnes propriétés des descripteurs locaux c'est-à-dire leur invariance vis-à-vis de transformations affines dans le plan image telles qu'une rotation, une translation ou un changement d'échelle.Nous utilisons ces graphes descripteurs dans le cadre de l'approche Sacs-de-Mots-Visuels. Le problème de définition d'une distance, ou dissimilarité, entre les graphes pour la classification non supervisée et la reconnaissance est nécessairement soulevé. Nous proposons une mesure de dissimilarité par le Noyau Dépendant du Contexte (Context-Dependent Kernel: CDK) proposé par H. Sahbi et montrons sa relation avec la norme classique L2 lors de la comparaison de graphes triviaux (les points SURF).Pour la reconnaissance d'activités par MMC, les expériences sont conduites sur le premier corpus au monde de vidéos avec caméra portée destiné à l'observation des d'IADL et sur des bases de données publiques comme SIVAL et Caltech-101 pour la reconnaissance d'objetsThe research of this PhD thesis is fulfilled in the context of wearable video monitoring of patients with aged dementia. The idea is to provide a new tool to medical practitioners for the early diagnosis of elderly dementia such as the Alzheimer disease. More precisely, Instrumental Activities of Daily Living (IADL) have to be indexed in videos recorded with a wearable recording device.Such videos present specific characteristics i.e. strong motion or strong lighting changes. Furthermore, the tackled recognition task is of a very strong semantics. In this difficult context, the first step of analysis is to define an equivalent to the notion of “shots” in edited videos. We therefore developed a method for partitioning continuous video streams into viewpoints according to the observed motion in the image plane.For the recognition of IADLs we developed a solution based on the formalism of Hidden Markov Models (HMM). A hierarchical HMM with two levels modeling semantic activities or intermediate states has been introduced. A complex set of features (dynamic, static, low-level, mid-level) was proposed and the most effective description spaces were identified experimentally.In the mid-level features for activities recognition we focused on the semantic objects the person manipulates in the camera view. We proposed a new concept for object/image description using local features (SURF) and the underlying semi-local connected graphs. We introduced a nested approach for graphs construction when the same scene can be described by levels of graphs with increasing number of nodes. We build these graphs with Delaunay triangulation on SURF points thus preserving good properties of local features i.e. the invariance with regard to affine transformation of image plane: rotation, translation and zoom.We use the graph features in the Bag-of-Visual-Words framework. The problem of distance or dissimilarity definition between graphs for clustering or recognition is obviously arisen. We propose a dissimilarity measure based on the Context Dependent Kernel of H. Sahbi and show its relation with the classical entry-wise norm when comparing trivial graphs (SURF points).The experiments are conducted on the first corpus in the world of wearable videos of IADL for HMM based activities recognition, and on publicly available academic datasets such as SIVAL and Caltech-101 for object recognition
31
McEleney, Sarah Nicole. "La influencia del conocimiento de otras lenguas en la identificación de palabras en español L2 un estudio de los modelos bia y bia+ /". Oxford, Ohio : Miami University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=miami1248105154.
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Dutoit, Denis. "Reconnaissance de mots isoles a travers le reseau telephonique". Paris, ENST, 1988. http://www.theses.fr/1988ENST0008.
Testo completoAbstract (sommario):
Etude et evaluation de performance d'algorithmes de reconnaissance de mots isoles avec de la parole de qualie telephonique (programmation dynamique et modeles de markov). Realisation d'un serveur vocal sur le reseau telephonique
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Orosanu, Luiza. "Reconnaissance de la parole pour l’aide à la communication pour les sourds et malentendants". Thesis, Université de Lorraine, 2015. http://www.theses.fr/2015LORR0172/document.
Testo completoAbstract (sommario):
Cette thèse fait partie du projet RAPSODIE dont l’objectif est de proposer une reconnaissance vocale spécialisée sur les besoins des personnes sourdes et malentendantes. Deux axes sont étudiées : la modélisation lexicale et l’extraction d’informations para-lexicales. Concernant la modélisation lexicale, nous avons étudié les modèles de langage hybrides combinant mots et syllabes, et nous avons proposé une nouvelle approche basée sur une notion de similarité entre mots pour l’ajout de nouveaux mots dans le modèle de langage. Concernant l’extraction d’informations para-lexicales, nous avons étudié l'utilisation des paramètres prosodiques, des paramètres linguistiques ou de leur combinaison pour la détection des questions et des affirmations. Cette détection a comme but de signaler aux personnes sourdes ou malentendantes quand une question leur est adresséeThis thesis is part of the RAPSODIE project which aims at proposing a speech recognition device specialized on the needs of deaf and hearing impaired people. Two aspects are studied: optimizing the lexical models and extracting para-lexical information. Regarding the lexical modeling, we studied hybrid language models combining words and syllables, and we proposed a new approach based on a similarity measure between words to add new words in the language model. Regarding the extraction of para-lexical information, we investigated the use of prosodic features, of linguistic features and of their combination for the detection of questions and statements. This detection aims to inform the deaf and hearing impaired people when a question is addressed to them
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Törnros, Micaela, e Maria Älloäng. "Brukardelaktighet i arbetet med insatsen gruppboende enligt LSS : En explorativ intervjustudie med LSS-handläggare och stödpersonal på gruppboende". Thesis, Stockholms universitet, Institutionen för socialt arbete, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-189579.
Testo completoAbstract (sommario):
Previous research shows that people with severe disabilities often are neglected in the work of enhancing user participation. It is shown that even though professionals increase the possibility for user participation in their work, it is not necessary that the users receive it. This study aims to show how professionals working for people with disabilities applies user participation in their everyday work. We used a qualitative exploratory method and interviewed ten social workers within service administration and supportive housing, located at three different municipalities in the region of Stockholm. Using Shier’s participation model in combination with theory of recognition we got similar results as previous research. The social workers have a great intention in enhancing user’s participation in their work, though organizational structures stand in their way. That drives them to use what is known as “silent knowledge”, a combination of their personality, previous experience and their ingenuity.
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Kenklies, Kai Malte. "Instructing workers through a head-worn Augmented Reality display and through a stationary screen on manual industrial assembly tasks : A comparison study". Thesis, Umeå universitet, Institutionen för informatik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172888.
Testo completoAbstract (sommario):
It was analyzed if instructions on a head-worn Augmented Reality display (AR-HWD) are better for manual industrial assembly tasks than instructions on a stationary screen. A prototype was built which consisted of virtual instruction screens for two example assembly tasks. In a comparison study participants performed the tasks with instructions through an AR-HWD and alternatively through a stationary screen. Questionnaires, interviews and observation notes were used to evaluate the task performances and the user experience. The study revealed that the users were excited and enjoyed trying the technology. The perceived usefulness at the current state was diverse, but the users saw a huge potential in AR-HWDs for the future. The task accuracy with instructions on the AR-HWD was equally good as with instructions on the screen. AR-HWDs are found to be a better approach than a stationary screen, but technological limitations need to be overcome and workers need to train using the new technology to make its application efficient.
36
Oger, Stanislas. "Modèles de langage ad hoc pour la reconnaissance automatique de la parole". Phd thesis, Université d'Avignon, 2011. http://tel.archives-ouvertes.fr/tel-00954220.
Testo completoAbstract (sommario):
Les trois piliers d'un système de reconnaissance automatique de la parole sont le lexique,le modèle de langage et le modèle acoustique. Le lexique fournit l'ensemble des mots qu'il est possible de transcrire, associés à leur prononciation. Le modèle acoustique donne une indication sur la manière dont sont réalisés les unités acoustiques et le modèle de langage apporte la connaissance de la manière dont les mots s'enchaînent.Dans les systèmes de reconnaissance automatique de la parole markoviens, les modèles acoustiques et linguistiques sont de nature statistique. Leur estimation nécessite de gros volumes de données sélectionnées, normalisées et annotées.A l'heure actuelle, les données disponibles sur le Web constituent de loin le plus gros corpus textuel disponible pour les langues française et anglaise. Ces données peuvent potentiellement servir à la construction du lexique et à l'estimation et l'adaptation du modèle de langage. Le travail présenté ici consiste à proposer de nouvelles approches permettant de tirer parti de cette ressource.Ce document est organisé en deux parties. La première traite de l'utilisation des données présentes sur le Web pour mettre à jour dynamiquement le lexique du moteur de reconnaissance automatique de la parole. L'approche proposée consiste à augmenter dynamiquement et localement le lexique du moteur de reconnaissance automatique de la parole lorsque des mots inconnus apparaissent dans le flux de parole. Les nouveaux mots sont extraits du Web grâce à la formulation automatique de requêtes soumises à un moteur de recherche. La phonétisation de ces mots est obtenue grâce à un phonétiseur automatique.La seconde partie présente une nouvelle manière de considérer l'information que représente le Web et des éléments de la théorie des possibilités sont utilisés pour la modéliser. Un modèle de langage possibiliste est alors proposé. Il fournit une estimation de la possibilité d'une séquence de mots à partir de connaissances relatives à 'existence de séquences de mots sur le Web. Un modèle probabiliste Web reposant sur le compte de documents fourni par un moteur de recherche Web est également présenté. Plusieurs approches permettant de combiner ces modèles avec des modèles probabilistes classiques estimés sur corpus sont proposées. Les résultats montrent que combiner les modèles probabilistes et possibilistes donne de meilleurs résultats que es modèles probabilistes classiques. De plus, les modèles estimés à partir des données Web donnent de meilleurs résultats que ceux estimés sur corpus.
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Hrouda, Debra R. "Factors Associated With Readiness For Treatment In A Sample Of Substance-Dependent, Trauma-Exposed Incarcerated Women". Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1401824178.
Testo completo
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Pešek, Milan. "Detekce logopedických vad v řeči". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218106.
Testo completoAbstract (sommario):
The thesis deals with a design and an implementation of software for a detection of logopaedia defects of speech. Due to the need of early logopaedia defects detecting, this software is aimed at a child’s age speaker. The introductory part describes the theory of speech realization, simulation of speech realization for numerical processing, phonetics, logopaedia and basic logopaedia defects of speech. There are also described used methods for feature extraction, for segmentation of words to speech sounds and for features classification into either correct or incorrect pronunciation class. In the next part of the thesis there are results of testing of selected methods presented. For logopaedia speech defects recognition algorithms are used in order to extract the features MFCC and PLP. The segmentation of words to speech sounds is performed on the base of Differential Function method. The extracted features of a sound are classified into either a correct or an incorrect pronunciation class with one of tested methods of pattern recognition. To classify the features, the k-NN, SVN, ANN, and GMM methods are tested.
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Sixtus, Achim [Verfasser]. "Across-word phoneme models for large vocabulary continuous speech recognition / vorgelegt von Achim Sixtus". 2003. http://d-nb.info/967058945/34.
Testo completo
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Kara, Kayikci Zöhre [Verfasser]. "Word recognition using hidden Markov models and neural associative memories / vorgelegt von Zöhre Kara Kayikci". 2008. http://d-nb.info/1000445275/34.
Testo completo
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Sundaram, Suresh. "Lexicon-Free Recognition Strategies For Online Handwritten Tamil Words". Thesis, 2011. http://etd.iisc.ernet.in/handle/2005/2363.
Testo completoAbstract (sommario):
In this thesis, we address some of the challenges involved in developing a robust writer-independent, lexicon-free system to recognize online Tamil words. Tamil, being a Dravidian language, is morphologically rich and also agglutinative and thus does not have a finite lexicon. For example, a single verb root can easily lead to hundreds of words after morphological changes and agglutination. Further, adoption of a lexicon-free recognition approach can be applied to form-filling applications, wherein the lexicon can become cumbersome (if not impossible) to capture all possible names. Under such circumstances, one must necessarily explore the possibility of segmenting a Tamil word to its individual symbols.
Modern day Tamil alphabet comprises 23 consonants and 11 vowels forming a total combination of 313 characters/aksharas. A minimal set of 155 distinct symbols have been derived to recognize these characters. A corpus of isolated Tamil symbols (IWFHR database) is used for deriving the various statistics proposed in this work. To address the challenges of segmentation and recognition (the primary focus of the thesis), Tamil words are collected using a custom application running on a tablet PC. A set of 10000 words (comprising 53246 symbols) have been collected from high school students and used for the experiments in this thesis. We refer to this database as the ‘MILE word database’.
In the first part of the work, a feedback based word segmentation mechanism has been proposed. Initially, the Tamil word is segmented based on a bounding box overlap criterion. This dominant overlap criterion segmentation (DOCS) generates a set of candidate stroke groups. Thereafter, attention is paid to certain attributes from the resulting stroke groups for detecting any possible splits or under-segmentations. By relying on feedbacks provided by
a priori knowledge of attributes such as number of dominant points and inter-stroke displacements the recognition label and likelihood of the primary SVM classifier
linguistic knowledge on the detected stroke groups, a decision is taken to correct it or not. Accordingly, we call the proposed segmentation as ‘attention feedback segmentation’ (AFS). Across the words in the MILE word database, a segmentation rate of 99.7% is achieved at symbol level with AFS. The high segmentation rate (with feedback) in turn improves the symbol recognition rate of the primary SVM classifier from 83.9% (with DOCS alone) to 88.4%.
For addressing the problem of segmentation, the SVM classifier fed with the x-y trace of the normalized and resampled online stroke groups is quite effective. However, the performance of the classifier is not robust to effectively distinguish between many sets of similar looking symbols. In order to improve the symbol recognition performance, we explore two approaches, namely reevaluation strategies and language models.
The reevaluation techniques, in particular, resolve the ambiguities in base consonants, pure consonants and vowel modifiers to a considerable extent. For the frequently confused sets (derived from the confusion matrix), a dynamic time warping (DTW) approach is proposed to automatically extract their discriminative regions. Dedicated to each confusion set, novel localized cues are derived from the discriminative region for their disambiguation. The proposed features are quite promising in improving the symbol recognition performance of the confusion sets. Comparative experimental analysis of these features with x-y coordinates are performed for judging their discriminative power. The resolving of confusions is accomplished with expert networks, comprising discriminative region extractor, feature extractor and SVM. The proposed techniques improve the symbol recognition rate by 3.5% (from 88.4% to 91.9%) on the MILE word database over the primary SVM classifier.
In the final part of the thesis, we integrate linguistic knowledge (derived from a text corpus) in the primary recognition system. The biclass, bigram and unigram language models at symbol level are compared in terms of recognition performance. Amongst the three models, the bigram model is shown to give the highest recognition accuracy. A class reduction approach for recognition is adopted by incorporating the language bigram model at the akshara level. Lastly, a judicious combination of reevaluation techniques with language models is proposed in this work. Overall, an improvement of up to 4.7% (from 88.4% to 93.1%) in symbol level accuracy is achieved.
The writer-independent and lexicon-free segmentation-recognition approach developed in this thesis for online handwritten Tamil word recognition is promising. The best performance of 93.1% (achieved at symbol level) is comparable to the highest reported accuracy in the literature for Tamil symbols. However, the latter one is on a database of isolated symbols (IWFHR competition test dataset), whereas our accuracy is on a database of 10000 words and thus, a product of segmentation and classifier accuracies. The recognition performance obtained may be enhanced further by experimenting on and choosing the best set of features and classifiers. Also, the word recognition performance can be very significantly improved by using a lexicon. However, these are not the issues addressed by the thesis. We hope that the lexicon-free experiments reported in this work will serve as a benchmark for future efforts.
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賴怡伶. "A Study of Children’s Word Recognition, Vocabulary Comprehension, and Discourse Comprehension: A Comparison of Three Curriculum Models". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/74212965059449191556.
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Ferreira, Taciana Sampaio Meneses. "Inventário de reconhecimento de palavras : estudos de validação". Master's thesis, 2011. http://hdl.handle.net/1822/17920.
Testo completoAbstract (sommario):
Dissertação de mestrado integrado em Psicologia (área de especialização em Psicologia Escolar e da Educação)A leitura é uma actividade complexa que exige a activação de muitos processos cognitivo-linguísticos, processos que se inter-relacionam e de entre os quais destacamos, como alvo de estudo, o reconhecimento de palavras. A variedade de definições contribui para o acesso a um vasto leque de conceitos acerca do que é o reconhecimento de palavras. Sendo o mais geral a conversão dos grafemas em padrões fonológicos, identificando através de um processo de descodificação a palavra escrita (Morais, 1997). O reconhecimento de palavras como parte dos processos de leitura ganha importância nas investigações actuais. Constata-se, no entanto, que a nível nacional ainda são poucos os instrumentos de avaliação validados e aferidos. É neste sentido que se inscreve a presente dissertação que tem como objectivo descrever a construção e validação do Inventário de Reconhecimento de Palavras – IRP. A prova consiste na leitura em voz alta de palavras que variam quanto à regularidade, frequência e extensão. É uma prova informatizada com recurso ao programa Superlab 4.0 que apresenta sequencialmente os 40 itens no ecrã. Durante a aplicação a resposta é registada como certa ou errada. A prova foi aplicada individualmente a 146 crianças do 2.º, 3.º e 4.º anos do 1.ºciclo, de um agrupamento de escolas da zona norte do país. Efectuaram-se análises estatísticas que revelaram um índice de dificuldade dos itens relativamente elevado, indicando a facilidade da prova. Os itens problemáticos foram excluídos, nas análises seguintes revelaram-se diferenças estatisticamente significativas entre os anos de escolaridade. Foram, ainda, encontradas correlações moderadas com a avaliação da leitura efectuada pelos professores e os resultados do PRP. Considerando a importância que o IRP apresentou na análise das características psicométricas das palavras enunciadas, sugere-se a continuidade da investigação na área ultrapassando as limitações aludidas.
Reading is a complex activity that requires activation of many cognitive-linguistic processes, processes that are interrelated and among whom, we highlight as the subject of study, recognition of words. The variety of definitions contributes to access to a wide range of concepts about what is word recognition. Being the most general the conversion of the graphemes in phonological patterns, identifying through a process of decoding the written word (Morais, 1997). The recognition of words as part of the reading process gains importance in currents researches. Nonetheless, it's a fact that there aren't, nationally, valid and standardized assessment instruments. In this way, is part of this dissertation aims to describe the construction and validation of the Word Recognition Inventory - WRI. The test consists of reading aloud words that vary in the regularity, frequency and extent. It is a computerized test using the program Superlab 4.0 which presents the 40 items on the screen. During application the answer is recorded as right or wrong. The test was applied individually to 146 children in second, third and fourth year of the first cycle, studying in a group of schools in the north of the country. Were carried out, statistical analysis revealed a level of difficulty of the items relatively high, giving evidence of the test easiness. The problem items were excluded, in the following analysis were revealed differences statistically significant between the years of schooling. We also found moderate correlations with the reading assessment conducted by teachers and the results of the PRP. Considering the importance of the WRI presented in the analysis of the psychometric characteristics of spoken words, it is suggested to continue the research on overcoming the limitations alluded to.
Fundação para a Ciência e a Tecnologia (FCT) - Projeto PTDC/PSI-EDU/098592/2008
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Stark, Robert John Alexander. "The influence of teaching hardwriting, reading and spelling skills on the accuracy of world level reading". Diss., 2010. http://hdl.handle.net/2263/27639.
Testo completoAbstract (sommario):
The purpose of the study was to investigate the influence of THRASS (Teaching Handwriting, Reading and Spelling Skills) on the word level accuracy skills of a group of grade 2 learners. Word level accuracy is one sub skill in learning to read and is an indicator of the word recognition abilities of the child. THRASS is a program that has been designed to systematically teach phonics and, thus, teaches the basic building blocks of word sounds and structure so as to improve the child’s decoding ability and word recognition ability. The research took place within the positivist paradigm and the methodology is quantitative in nature. The data collection method took the form of a one group pretest-posttest design, where a standardised reading test was administered prior to exposing the participants to the THRASS Program and then readministered one year later on the same group of learners. Data analysis took the form of statistical analysis to investigate any statistical significant difference in the word level accuracy skills of those Grade 2 learners. The result showed that over the period of a year the average reading accuracy age for the target population increased by four months. However, after statistical analysis the difference was not statistically significant. The Null Hypothesis that; exposing a group of Grade 2 learners to the THRASS Program for a period of one year will have no statistically significant influence on their word level accuracy skills cannot be rejected . However, the changes both in average reading accuracy as well as error patterns have inspired recommendations for further research. CopyrightDissertation (MEd)--University of Pretoria, 2010.
Educational Psychology
unrestricted
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Aziz, Afssá Abdul. "Estudo comparativo sobre os desempenhos em leitura nos 1º e 2º anos de escolaridade do ensino básico". Master's thesis, 2010. http://hdl.handle.net/10400.12/4339.
Testo completoAbstract (sommario):
Dissertação de Mestrado apresentada ao ISPA - Instituto UniversitárioO presente estudo teve como objectivos analisar os desempenhos em leitura oral de palavras, analisar os tipos de erros dados por crianças em início de escolaridade e tentar perceber se a leitura de palavras e o reconhecimento ortográfico de palavras se correlacionam positivamente. Participaram neste estudo 222 crianças de ambos os sexos que frequentavam os dois primeiros anos de escolaridade de uma escola pública a norte do país e duas escolas privadas, sendo uma delas da região do norte e outra da região do centro. Foi aplicada individualmente uma Prova de Leitura Oral de Palavras e foi aplicada em grupo uma Prova de Selecção Ortográfica (Martins & Simões, 2008). Os resultados evidenciaram que existem diferenças significativas entre os anos de escolaridade no desempenho das duas provas que foram aplicadas. Na análise dos tipos de erros da Prova de Leitura Oral de Palavras, foram encontradas diferenças significativas entre os dois anos de para os erros contextuais, erros fonéticos, adições, supressões, inversões, erros de acentuação, erros visuais e para os erros múltiplos; quanto à percentagem de erros, foram encontradas diferenças significativas entre os dois anos nos erros Visuais. Na análise dos tipos de erros e na percentagem de erros da Prova de Selecção Ortográfica, foram encontradas diferenças significativas entre os dois anos para os erros homófonos e para os erros graficamente semelhantes. Verificou-se, ainda, que existe uma correlação positiva entre a leitura e o reconhecimento ortográfico, sendo esta correlação mais forte no 2º ano de escolaridade.
ABSTRACT: The present study had the intent to analyze oral word reading performances, analyze types of errors made by children in early education and try to see whether word reading and word spelling recognition are positively correlated. This study includes 222 children of both sexes who have attended the first two years of schooling of a public school in the north of country and two private schools, being one of the northern region and one of the central region. it was administered individually an Oral Word Reading Test and was applied in group a Spell Selection Test (Martins & Simões, 2008). The results showed that the perfornance of the tests that were applied were significantly different between the two first grades. In the analysis of the error types in the Oral Word Reading Test, significant differences were found in Contextual Errors, Phonetic Errors, Additions, Deletions, Inversions, Accentuation Errors, Visual errors, and Multiple Errors, between the two grades; as for the error percentage, significant differences were found in Visual errors between the two grades. In the analysis of errors and the percentage of errors of the Spell Selection Test, significant differences were found in homophone errors and graphically similar errors, between the two grades. It was verified that there is a positive correlation between reading and spelling recognition and this correlation is more significant in participantes from the second grade.
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Lief, Eric. "Použití hlubokých kontextualizovaných slovních reprezentací založených na znacích pro neuronové sekvenční značkování". Master's thesis, 2019. http://www.nusl.cz/ntk/nusl-393167.
Testo completoAbstract (sommario):
A family of Natural Language Processing (NLP) tasks such as part-of- speech (PoS) tagging, Named Entity Recognition (NER), and Multiword Expression (MWE) identification all involve assigning labels to sequences of words in text (sequence labeling). Most modern machine learning approaches to sequence labeling utilize word embeddings, learned representations of text, in which words with similar meanings have similar representations. Quite recently, contextualized word embeddings have garnered much attention because, unlike pretrained context- insensitive embeddings such as word2vec, they are able to capture word meaning in context. In this thesis, I evaluate the performance of different embedding setups (context-sensitive, context-insensitive word, as well as task-specific word, character, lemma, and PoS) on the three abovementioned sequence labeling tasks using a deep learning model (BiLSTM) and Portuguese datasets. v
47
Jue-Wen, Liu, e 劉志文. "Research of Isolated-Word Recognition Using Hidden Markov Model". Thesis, 1995. http://ndltd.ncl.edu.tw/handle/97648683530887214875.
Testo completoAbstract (sommario):
碩士國立交通大學
資訊科學學系
83
Speech recognition plays an important role in computer science because the voice input to computers has the advantages of of offers fast, hands free, eyes free and location free. The communication with computers can be carried out convenient without the use keyboards or mouse. Hidden Markov models(HMM) has been using widely in many computers science areas, especially in the area of speech recognition. In this theis, the basic theories and algorithms about HMM are described in detail. Consequently, an isolated-word speech recognition system based on HMM is implemented in this thesis research. Applications of the implemented system in (1)isolated-word recognition for Mandarin, and (2)speaker identification is investigated. Satisfactory results have been obtained for some simple cases, e.g. small vocabulary, small number of speakers, etc. Possible extension of the research results to solve more general speech recognition problems is briefly discussed.
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Huang, Eric, e 黃世中. "Using the Word-based Triphone Model for Continuous-Speech Recognition". Thesis, 1996. http://ndltd.ncl.edu.tw/handle/30363400193651123128.
Testo completo
49
Liao, Sheng-Wen, e 廖陞汶. "Design of Isolated Word Recognition Based on Hidden Markov Model". Thesis, 1999. http://ndltd.ncl.edu.tw/handle/75841343046835186007.
Testo completoAbstract (sommario):
碩士國立成功大學
電機工程學系
87
The left-to-right continuous hidden Markov model (CHMM) with kernel using the viterbi algorithm has successfully been used for speech recognition in the past years. The viterbi algorithm includes two main tasks. One is the Gaussian calculation and the other is the optimal estimation of state path. However, general processor can not efficiently process the variance of arithmetic operations. We must design a VLSI hardware architecture of high speed to overcome the problem. In this thesis, we use the data scheduling method to create the architecture implementing the viterbi algorithm. The design is divided into Gaussian module and viterbi-kernel module to reduce the complexity of design. We implement the system by using standard cells technology. Experimental results show our method is effective.
50
Basavaraja, S. V. "Robust Techniques Of Language Modeling For Spoken Language Identification". Thesis, 2007. http://hdl.handle.net/2005/571.
Testo completoAbstract (sommario):
Language Identification (LID) is the task of automatically identifying the language of speech signal uttered by an unknown speaker. An N language LID task is to classify an input speech utterance, spoken by an unknown speaker and of unknown text, as belonging to one of the N languages L1, L2, . . , LN.
We present a new approach to spoken language modeling for language identification using the Lempel-Ziv-Welch (LZW) algorithm, with which we try to overcome the limitations of n-gram stochastic models by automatically identifying the valid set of variable length patterns from the training data. However, since several patterns in a language pattern table are also shared by other language pattern tables, confusability prevailed in the LID task. To overcome this, three pruning techniques are proposed to make these pattern tables more language specific. For LID with limited training data, we present another language modeling technique, which compensates for language specific patterns missing in the language specific LZW pattern table. We develop two new discriminative measures for LID based on the LZW algorithm, viz., (i) Compression Ratio Score (LZW-CRS) and (ii) Weighted Discriminant Score (LZW-WDS). It is shown that for a 6-language LID task of the OGI-TS database, the new model (LZW-WDS) significantly outperforms the conventional bigram approach.
With regard to the front end of the LID system, we develop a modified technique to model for Acoustic Sub-Word Units (ASWU) and explore its effectiveness. The segmentation of speech signal is done using an acoustic criterion (ML-segmentation). However, we believe that consistency and discriminability among speech units is the key issue for the success of ASWU based speech processing. We develop a new procedure for clustering and modeling the segments using sub-word GMMs. Because of the flexibility in choosing the labels for the sub-word units, we do an iterative re-clustering and modeling of the segments. Using a consistency measure of labeling the acoustic segments, the convergence of iterations is demonstrated. We show that the performance of new ASWU based front-end and the new LZW based back-end for LID outperforms the earlier reported PSWR based LID.