In this thesis, a three-word and four-word Mandarin phrases speech recognition system is developed. This system contains two recordings of twenty-four thousand three-word phrases and twenty-two thousand four-word phrases in the database. And it applies MFCC, mono-syllable HMM¡¦s and speech-text alignment scheme to select the initial phrase candidates. A wavelet transform based vowel segmentation technique and a Mandarin pitch identification method is then followed to increase the phrase correct identification rate and obtain the final answer. Experimental results indicate that 92% and 96% correct rates can be achieved for three-word and four-word phrases recognition problems respectively, under the conditions that the first recording of this database is used for training and the second one is for testing. For the speaker-dependent case, the correct phrase can be found within 1 second, using a PC with Intel Celeron 2.4 GHz CPU and RedHat Linux 9.0 Operation System.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-02-02T13:30:50Z No. of bitstreams: 1 EmmanuelDuarteBarbosa_DISSERT.pdf: 9706329 bytes, checksum: cf979f942793c968afbd04719854d7f0 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-02-08T19:26:36Z (GMT) No. of bitstreams: 1 EmmanuelDuarteBarbosa_DISSERT.pdf: 9706329 bytes, checksum: cf979f942793c968afbd04719854d7f0 (MD5) / Made available in DSpace on 2017-02-08T19:26:36Z (GMT). No. of bitstreams: 1 EmmanuelDuarteBarbosa_DISSERT.pdf: 9706329 bytes, checksum: cf979f942793c968afbd04719854d7f0 (MD5) Previous issue date: 2016-07-29 / A enzima Delta Aminolevul?nico Desidratase (ALAD) ? uma metaloprote?na citos?lica essencial em v?rios processos biol?gicos, uma vez que ? respons?vel pelo segundo passo da cat?lise enzim?tica na forma??o de porfobilinog?nio, um precursor dos tetrapirr?licos (heme, clorofila). Esta enzima ? bastante sens?vel a metais pesados e tem sido classicamente usada como um marcador na intoxica??o por chumbo. Sua inibi??o se d? pela substitui??o desses metais pesados no s?tio de liga??o a metais. Na ALAD humana, o Zinco (Zn2+) ocupa funcionalmente este s?tio sendo essencial para a coordena??o das cadeias de ?cido aminolevul?nico durante a cat?lise enzim?tica. Embora muitos ensaios in vitro, in vivo e in s?lico j? tenham demonstrado a import?ncia do Zn2+ nesse s?tio, n?o se tinha conhecimento de nenhum estudo baseado em abordagem qu?ntica com o intuito de elucidar esta intera??o de forma mais detalhada. Diante disso, o presente trabalho teve como objetivo analisar as muta??es missense que acometem o s?tio de liga??o ao zinco e descrever atrav?s de m?todos qu?nticos a energia de intera??o entre a enzima e o zinco com maior acur?cia utilizando o m?todo do Fracionamento Molecular com Capas Conjugadas (MFCC), quantificando energeticamente os res?duos de amino?cidos posicionados at? uma dist?ncia de 8,5 ? do centroide do ligante. Foi identificado as altera??es bioqu?micas na estrutura monom?rica dos mutantes, as quais resultam na diminui??o da atividade enzim?tica. Foram identificados um total de 30 res?duos com valores energ?ticos variados que interagem com o zinco no bols?o de liga??o. Aqueles que apresentaram valores significativos (de atra??o ou repuls?o) e est?o relacionados funcionalmente ? atividade enzim?tica foram: Lis199, Lis252, Arg 209, Arg 174, Cis122, Cis124 e Cis132; e aqueles que demonstraram relev?ncia para a perman?ncia do ?on no s?tio de liga??o foram: Asp169, Gli130, Gli133, Asp120 e Ser168. A partir disso, p?de-se concluir que al?m dos grupos nucle?filos (grupos tiolatos) dos res?duos Cis122, Cis124 e Cis132, os res?duos Asp169, Asp120 e Ser168 s?o fundamentais na composi??o do bols?o, uma vez que demonstraram grande quantidade de energia de intera??o atrativa com o ?on Zn2+. / The enzyme Delta Aminolevulinic Dehydratase (ALAD) is a cytosolic metalloproteinase essential in several biological processes since it participates in the second step in porphobilinogen formation pathway, a tetrapyrrolic precursor of heme and chlorophyll. This enzyme is very sensitive to heavy metals and has traditionally been used as a biomarker in lead poisoning. Its inhibition occurs when these heavy metals are replaced inside the metal binding site. In human ALAD, Zinc (Zn2+) functionally occupies this site and it is essential for coordination of two chains of aminolevulinic acid for the enzymatic catalysis. Although many in vitro, in vivo and in silico works have already demonstrated the importance of Zn2+ at that site, to the best of our knowledge, there isn?t any studies on literature based on quantum approach in order to elucidate this interactions in more details. Therefore, the aim of the present study was to analyse the missense mutations that affect the zinc binding site and describe through quantum methods the energy interaction between zinc and ALAD with greater accuracy using the method of Molecular fractionation with conjugated caps (MFCC) by quantifying amino acid residues? energy positioned at 8.5 ? of distance with the ligand centroid. It was identified biochemical changes in the monomeric structure of mutants, which result in decreased enzyme activity. It were identified a total of 30 residues with a wide range of energy values. The residues with significant (atractition or repulsion) values and functionally related to enzymatic activity were: Lys199, Lys252, Cys122, Cys124 and Cys132; and those that demonstrated relevance to the ion permanence inside the binding site were: Asp169, Gly130, Gly133, Asp120 and Ser168. Thus, it could be concluded that in addition to the nucleophilic groups (thiolates groups) from Cys122, Cys124 and Cys132, others residues such as Asp169, Asp120 and Ser168 are fundamental in the catalytic pocket composition, since they showed high attractive interaction energy with Zn2+ ion.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-10-04T22:23:59Z No. of bitstreams: 1 DalilaNascimentoManso_DISSERT.pdf: 1914411 bytes, checksum: 966fc442e252d656c3946bff697a75f5 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-10-13T21:33:08Z (GMT) No. of bitstreams: 1 DalilaNascimentoManso_DISSERT.pdf: 1914411 bytes, checksum: 966fc442e252d656c3946bff697a75f5 (MD5) / Made available in DSpace on 2017-10-13T21:33:08Z (GMT). No. of bitstreams: 1 DalilaNascimentoManso_DISSERT.pdf: 1914411 bytes, checksum: 966fc442e252d656c3946bff697a75f5 (MD5) Previous issue date: 2017-04-19 / A mais recente pandemia do v?rus influenza ocorreu no ano de 2009, causada pela cepa do influenza A (H1N1), e popularmente conhecida como gripe A ou gripe su?na, gerou preocupa??o aos ?rg?os mundiais de sa?de. Com um quadro sintom?tico que inclui febre, tosse, inflama??o na garganta na maioria dos casos, alguns pacientes, principalmente imunossuprimidos que podem apresentar complica??es que evoluem ao ?bito. A transmiss?o do v?rus ocorre atrav?s do contato entre pessoa a pessoa e seu mecanismo de infec??o se d? a partir das duas glicoprote?nas de superf?cie, a hemaglutinina e a neuraminidase. A hemaglutinina atua se ligando aos receptores do ?cido si?lico favorecendo a entrada do v?rus nas c?lulas-alvo e a neuraminidase cliva as c?lulas do receptor de res?duos do ?cido si?lico, onde as novas part?culas virais est?o se ligando. Atrav?s dessa quebra haver? libera??o das novas part?culas virais, que atrav?s da hemaglutinina invadir?o novas c?lulas. Baseado nisso, f?rmacos foram desenvolvidos com intuito de inibir a a??o da neuraminidase, os chamados inibidores da neuraminidase que interferem na libera??o dessas novas part?culas virais evitando a dissemina??o da infec??o no trato respirat?rio. Dentre estes inibidores o oseltamivir ? o f?rmaco de escolha para profilaxia e tratamento da gripe A; por?m, relatos de resist?ncia a esse f?rmaco foram descritos, o que causou preocupa??o nos profissionais da sa?de e governantes. A muta??o mais encontrada ? a HIS275TIR, onde a histidina ? substitu?da por uma tirosina, promovendo uma s?rie de altera??es conformacionais que diminuem a afinidade do f?rmaco pelo v?rus originando a resist?ncia. A partir da obten??o de dados cristalogr?ficos e simula??o computacional, calculamos a energia de intera??o da neuraminidase selvagem e com a presen?a da muta??o HIS275TIR ligadas ao oseltamivir utilizando a Teoria Funcional da Densidade (DFT) e do M?todo de Fracionamento Molecular com Capas Conjugadas (MFCC). Obtivemos 115 res?duos de intera??o para a neuraminidase selvagem (cristal 4B7R) e 109 res?duos de intera??o para o cristal com a neuraminidase mutante (3CL0). Os resultados foram avaliados de acordo com a relev?ncia dos valores energ?ticos para energias repulsivas e energias atrativas. Os c?lculos energ?ticos realizados confirmaram a redu??o da afinidade da cepa contendo a muta??o HIS275TIR e destacaram a import?ncia energ?tica do s?tio ativo da neuraminidase mostrando que os principais res?duos energ?ticos s?o encontrados nele tornando um alvo para obten??o de novos f?rmacos devido a sua conserva??o. As altera??es causadas pela substitui??o do amino?cido histidina por uma tirosina levaram a uma s?rie de mudan?as conformacionais nos amino?cidos vizinhos que provocaram altera??es eletrost?ticas resultando na resist?ncia ao f?rmaco. A partir desse estudo ser? poss?vel conhecer melhor as intera??es moleculares da neuraminidase mutante e posteriormente projetar novos designs de f?rmacos para serem elaborados e se tornarem mais eficientes na intera??o com as cepas mutantes desse v?rus. / The latest influenza pandemic occurred in the year 2009, caused by the strain of influenza A (H1N1), and popularly known as influenza A or swine flu, generated concern to the global health agencies. With a symptomatic picture that includes fever, cough, throat inflammation in most cases, some patients, mainly immunosuppressed, that can to present complications that evolve to death. Transmission of the virus takes place through contact between person to person and its mechanism of infection occurs from the two surface glycoproteins, hemagglutinin and neuraminidase. The hemagglutinin acts by binding to the sialic acid receptors favoring the entry of the virus into the target cells and the neuraminidase cleaves the receptor cells of sialic acid residues, where the new viral particles are binding. Through this breakdown there will be release of the new particles that through hemagglutinin will attack new cells. Based on these, drugs were developed in an attempt to inhibit the action of neuraminidase, so called neuraminidase inhibitors that interfere in the release of these new viral particles avoiding the spread of infection in the respiratory tract. Among the inhibitors, oseltamivir is the drug of choice for prophylaxis and treatment of influenza A, but reports of resistance to this drug have been described, which has caused concern in health professionals and rulers. The HIS275TIR mutation is most commonly found, where histidine is replaced by a tyrosine, promoting a series of conformational changes that decrease the affinity of the drug for the virus causing resistance. Based on crystallographic data and computational simulation, we calculated the interaction energy of the wild neuraminidase and the presence of the HIS275TIR mutation bonded to oseltamivir using the Functional Density Theory (DFT) and the Molecular Fractionation with Conjugated Caps (MFCC). We obtained 115 interaction residues for the wild neuraminidase (4B7R crystal) and 109 interaction residues for the crystal with the mutant neuraminidase (3CL0). The results were evaluated according to the relevance of the energy values for repulsive energies and attractive energies. The energetic calculations confirmed the reduction of the affinity of the strain containing the HIS275TIR mutation and highlighted the energy importance of the active site of the neuraminidase, showing that the main energy residues are found in it becoming a target for obtaining new drugs due to its conservation. The changes caused by the substitution of the amino acid histidine for a tyrosine led to a series of conformational changes in the neighboring amino acids that provoked electrostatic changes resulting in the resistance to the drug. From this study, it will be possible to know better the molecular interactions of the mutant neuraminidase and subsequently to project new drugs designs to be elaborated and become more efficient in the interaction with the mutant strains of this virus.

Submitted by João Arthur Martins (joao.arthur@ufpe.br) on 2015-03-10T19:07:24Z No. of bitstreams: 2 Dissertaçao Hesdras Viana.pdf: 2998238 bytes, checksum: de42b675472ac4632a3a3c04688a77d5 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Approved for entry into archive by Daniella Sodre (daniella.sodre@ufpe.br) on 2015-03-10T19:43:06Z (GMT) No. of bitstreams: 2 Dissertaçao Hesdras Viana.pdf: 2998238 bytes, checksum: de42b675472ac4632a3a3c04688a77d5 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-03-10T19:43:06Z (GMT). No. of bitstreams: 2 Dissertaçao Hesdras Viana.pdf: 2998238 bytes, checksum: de42b675472ac4632a3a3c04688a77d5 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2013-02-26 / Extrair características da fala é uma etapa fundamental para os sistemas de reconhecimento de voz. É através dos descritores que extraímos a energia do sinal, a frequência fundamental (pitch) e a estrutura dos formantes que serão utilizados como identificadores para cada palavra pronunciada. Descritores como MFCC (Mel-Frequency Cepstral Coefficient), RASTA-PLP (RelAtive SpecTrAl - Perceptual Linear Predictive) e PNCC (Power Normalized Cepstral Coefficient) são muitos utilizados no estado da arte na área de reconhecimento de voz, porém, essas técnicas não conseguem apresentar bons resultados quando expostos a amostras com presença de ruído, variabilidade de locutor e fala contínua. O objetivo deste trabalho é desenvolver um descritor para a fala que seja invariante ao ruído, ambiente e locução. Para isso, fizemos um estudo dos descritores de voz mais utilizados na literatura, identificando as vantagens e desvantagens, expondo a situações variadas. Para avaliação das técnicas, utilizamos a base NOIZEUS (Noisy Speech Corpus) e dois classificadores: HMM (Hidden Markov Models) e SVM (Support Vector Machine). Essa base tem como característica a presença de ruído variando de 0dB, 5dB, 10dB e 15dB, gravada em diversos ambientes. A utilização dos classificadores serviu para validar os descritores de voz. O descritor proposto, chamado de MINERS (Model Invariant to Noise and Environment and Robust for Speech), apresentou melhores resultados entre todos os descritores avaliados (MFCC, MFCC combinado com Wavelet Denoising, RASTAPLP e PNCC). A abordagem que obteve maior sucesso foi a utilização do MINERS com o classificador SVM.

The master thesis is divided into two parts theoretical and practical. The theoretical part is focused on methods of analysis and detection of speech signals. In the practical part the system for isolated word recognition was created in Matlab. The system is speaker independent separately for men and women. Also two speech databases were created for further use in the aircraft cockpit. Tests and evaluations were performed even with added noise.

Abstract A Keyword Spotting System (KWS) is a system that recognizes predefined keywords in spoken utterances or written documents. The objective is to obtain the highest possible keyword detection rate without increasing the number of false detections in a system. The common approach to keyword spotting is the use of a Hidden Markov Model (HMM). These are usually complex systems which require training speech data. The Typical HMM approach uses garbage templates or HMM models to match non-keyword speech and non-speech sounds. The purpose of this research is to design a simple Keyword Spotting System. The system will be designed to spot English words and should be easily adaptable to other languages There are many challenges in designing a keyword spotting system such as variations in speech like pitch, loudness, timbre that make recognition difficult. There can be wide variations in utterances even from the same speaker. In this research, the use of cross-correlation, as an alternative means for detecting keywords in an utterance, was investigated. This research also involves the modeling of a global keyword using a quantized dynamic time warping algorithm, which can function effectively with multi-speakers. The global keyword is an aggregation of the features from several occurrences of the same keyword. This research also investigates the effect of pitch normalization on keyword detection. The use of cross-correlation as a method for keyword spotting was investigated in both the time and MFCC domain. In the time domain the global keyword was cross-correlated with a pitch-normalized utterance. A zero lag ratio (the ratio of the power around the zero lag obtained from a cross correlation to the power in the rest of the signal is computed) was computed for each speech frame, a threshold was then used to determine if the keyword is present. For the MFCC domain the MFCC features of each keyword were computed, normalized and cross-correlated with the normalized MFCC features of portions of the utterance of the same size as the keyword. Cross-correlation of MFCC features of the keyword with that of each portion of the utterance yields a single value between 0-1. The portion with the highest value is usually the location of the keyword. Results in the time domain varied from keyword to keyword, some words showed a 60% hit rate while the average obtained from various keywords from the Call Home database had an average of 41%. Cross-correlation of the keywords and utterance in the MFCC domain yielded a 66% hit rate in test conducted on all different keywords in the Call Home and Switchboard corpus. The system accuracy is keyword dependent with some keywords having an 85% hit rate / Electrical and Computer Engineering

Made available in DSpace on 2015-04-11T14:03:17Z (GMT). No. of bitstreams: 1 DISSERTACAO ADRIANO NOGUEIRA.pdf: 382280 bytes, checksum: fc1f9e0caac3d97ff74a893e97298a71 (MD5) Previous issue date: 2008-12-17 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Digital processing of speech signal is applied in several computer applications, which the major ones are the following: Recognition, synthesis and coding of speech. All these applications require the amount of data in the acoustic signal to be reduced, in order to allow processing by a computer device. The feature extraction of speech signal, that is the goal of this study, performs this action. The features extracted should well depict the speech signal and should have no redundancy, in order to increase the performance of the systems using them. The feature extraction Mel Frequency Cepstral Coefficients (MFCC) method partially fulfills these requirements, but it is seriously damaged when noise signal is acting. The appliance of the statistical method of Factorial Analysis is intended to filter the noise components from the speech. The results of the experiments performed in this work shows that this is a competitive method, especially when used to generate acoustic models in severe noise conditions. / O processamento digital do sinal de voz é empregado em diversas aplicações computacionais, das quais as principais são: Reconhecimento, síntese e codificação da fala. Todas estas aplicações requerem que ocorra redução da quantidade de informações da onda acústica, de maneira a permitir o processamento por um computador. O processo de extração de características do sinal de voz, objeto de estudo deste trabalho, realiza esta tarefa. As características extraídas devem caracterizar o sinal de voz e não conter redundância, de forma a maximizar o desempenho dos sistemas que as utilizem. O método MFCC (Mel Frequency Cepstral Coefficients) de extração de características cumpre parcialmente esses requisitos, mas é seriamente degradado sob a incidência de ruído. A aplicação do método estatístico de Análise Fatorial objetiva filtrar o sinal de ruído das locuções. Os resultados obtidos dos experimentos realizados indicam a competitividade deste método, especialmente quando usado na geração dos modelos acústicos robustos em condições de ruído severo.

Sistema de reconhecimento de fala tem amplo emprego no universo industrial, no aperfeiçoamento de operações e procedimentos humanos e no setor do entretenimento e recreação. O objetivo específico do trabalho foi conceber e desenvolver um sistema de reconhecimento de voz, capaz de identificar comandos de voz, independentemente do locutor. A finalidade precípua do sistema é controlar movimentos de robôs, com aplicações na indústria e no auxílio de deficientes físicos. Utilizou-se a abordagem da tomada de decisão por meio de uma rede neural treinada com as características distintivas do sinal de fala de 16 locutores. As amostras dos comandos foram coletadas segundo o critério de conveniência (em idade e sexo), a fim de garantir uma maior discriminação entre as características de voz, e assim alcançar a generalização da rede neural utilizada. O préprocessamento consistiu na determinação dos pontos extremos da locução do comando e na filtragem adaptativa de Wiener. Cada comando de fala foi segmentado em 200 janelas, com superposição de 25% . As features utilizadas foram a taxa de cruzamento de zeros, a energia de curto prazo e os coeficientes ceptrais na escala de frequência mel. Os dois primeiros coeficientes da codificação linear preditiva e o seu erro também foram testados. A rede neural empregada como classificador foi um perceptron multicamadas, treinado pelo algoritmo backpropagation. Várias experimentações foram realizadas para a escolha de limiares, valores práticos, features e configurações da rede neural. Os resultados foram considerados muito bons, alcançando uma taxa de acertos de 89,16%, sob as condições de pior caso da amostragem dos comandos. / Systems for speech recognition have widespread use in the industrial universe, in the improvement of human operations and procedures and in the area of entertainment and recreation. The specific objective of this study was to design and develop a voice recognition system, capable of identifying voice commands, regardless of the speaker. The main purpose of the system is to control movement of robots, with applications in industry and in aid of disabled people. We used the approach of decision making, by means of a neural network trained with the distinctive features of the speech of 16 speakers. The samples of the voice commands were collected under the criterion of convenience (age and sex), to ensure a greater discrimination between the voice characteristics and to reach the generalization of the neural network. Preprocessing consisted in the determination of the endpoints of each command signal and in the adaptive Wiener filtering. Each speech command was segmented into 200 windows with overlapping of 25%. The features used were the zero crossing rate, the short-term energy and the mel-frequency ceptral coefficients. The first two coefficients of the linear predictive coding and its error were also tested. The neural network classifier was a multilayer perceptron, trained by the backpropagation algorithm. Several experiments were performed for the choice of thresholds, practical values, features and neural network configurations. Results were considered very good, reaching an acceptance rate of 89,16%, under the `worst case conditions for the sampling of the commands.

Dialectal Arabic speech research suffers from the lack of labelled resources and standardised orthography. There are three main challenges in dialectal Arabic speech recognition: (i) finding labelled dialectal Arabic speech data, (ii) training robust dialectal speech recognition models from limited labelled data and (iii) evaluating speech recognition for dialects with no orthographic rules. This thesis is concerned with the following three contributions: Arabic Dialect Identification: We are mainly dealing with Arabic speech without prior knowledge of the spoken dialect. Arabic dialects could be sufficiently diverse to the extent that one can argue that they are different languages rather than dialects of the same language. We have two contributions: First, we use crowdsourcing to annotate a multi-dialectal speech corpus collected from Al Jazeera TV channel. We obtained utterance level dialect labels for 57 hours of high-quality consisting of four major varieties of dialectal Arabic (DA), comprised of Egyptian, Levantine, Gulf or Arabic peninsula, North African or Moroccan from almost 1,000 hours. Second, we build an Arabic dialect identification (ADI) system. We explored two main groups of features, namely acoustic features and linguistic features. For the linguistic features, we look at a wide range of features, addressing words, characters and phonemes. With respect to acoustic features, we look at raw features such as mel-frequency cepstral coefficients combined with shifted delta cepstra (MFCC-SDC), bottleneck features and the i-vector as a latent variable. We studied both generative and discriminative classifiers, in addition to deep learning approaches, namely deep neural network (DNN) and convolutional neural network (CNN). In our work, we propose Arabic as a five class dialect challenge comprising of the previously mentioned four dialects as well as modern standard Arabic. Arabic Speech Recognition: We introduce our effort in building Arabic automatic speech recognition (ASR) and we create an open research community to advance it. This section has two main goals: First, creating a framework for Arabic ASR that is publicly available for research. We address our effort in building two multi-genre broadcast (MGB) challenges. MGB-2 focuses on broadcast news using more than 1,200 hours of speech and 130M words of text collected from the broadcast domain. MGB-3, however, focuses on dialectal multi-genre data with limited non-orthographic speech collected from YouTube, with special attention paid to transfer learning. Second, building a robust Arabic ASR system and reporting a competitive word error rate (WER) to use it as a potential benchmark to advance the state of the art in Arabic ASR. Our overall system is a combination of five acoustic models (AM): unidirectional long short term memory (LSTM), bidirectional LSTM (BLSTM), time delay neural network (TDNN), TDNN layers along with LSTM layers (TDNN-LSTM) and finally TDNN layers followed by BLSTM layers (TDNN-BLSTM). The AM is trained using purely sequence trained neural networks lattice-free maximum mutual information (LFMMI). The generated lattices are rescored using a four-gram language model (LM) and a recurrent neural network with maximum entropy (RNNME) LM. Our official WER is 13%, which has the lowest WER reported on this task. Evaluation: The third part of the thesis addresses our effort in evaluating dialectal speech with no orthographic rules. Our methods learn from multiple transcribers and align the speech hypothesis to overcome the non-orthographic aspects. Our multi-reference WER (MR-WER) approach is similar to the BLEU score used in machine translation (MT). We have also automated this process by learning different spelling variants from Twitter data. We mine automatically from a huge collection of tweets in an unsupervised fashion to build more than 11M n-to-m lexical pairs, and we propose a new evaluation metric: dialectal WER (WERd). Finally, we tried to estimate the word error rate (e-WER) with no reference transcription using decoding and language features. We show that our word error rate estimation is robust for many scenarios with and without the decoding features.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / As doenÃas cardiovasculares (CVDs) compreendem um amplo espectro de doenÃas do coraÃÃo e vasos sanguÃneos (artÃrias e veias), entre as quais se incluem a doenÃa das artÃrias coronÃrias, o ataque cardÃaco, a angina, a sÃndrome coronariana aguda, o aneurisma da aorta, arritmias cardÃacas, a doenÃa cardÃaca congÃnita, a insuficiÃncia cardÃaca e a doenÃa cardÃaca reumÃtica. Entre os principias fÃrmacos que tratam as doenÃas cardiovasculares estÃo: (i) as estatinas, que atuam inibindo a 3-hidroxi-3-metilgluratil coenzima A (HMG-CoA) redutase no processo de conversÃo da HMG-CoA em mevalonato, numa das etapas da biossÃntese do colesterol. Observa-se em ensaios clÃnicos que a aÃÃo das estatinas pode diminuir os nÃveis de colesterol de baixa densidade (LDL) entre 20\% e 60\%, reduzindo os eventos coronarianos em atà 1/3 no perÃodo de cinco anos; (ii) a aspirina, com a qual hà mais de 400 preparaÃÃes nos EUA e se produz cerca de 20 mil toneladas anualmente. ApÃs mais de um sÃculo de prÃtica clÃnica, a aspirina continua sendo a droga antitrombÃtica, antitÃrmica, analgÃsica e antiproliferativa mais amplamente recomendada. Ela age bloqueando a biossÃntese de hormÃnios inflamatÃrios prostanÃides atravÃs da inibiÃÃo das enzimas ciclooxigenase COX-1 e COX-2; (iii) os anti-hipertensivos, para os quais a Enzima Conversora de Angiotensina (ECA) à o principal alvo (inibidores da ECA estÃo no mercado a mais de 20 anos) visando o combate das pressÃes arteriais elevadas, que provocam alteraÃÃes nos vasos sanguÃneos e na musculatura do coraÃÃo, e levam a hipertrofia do ventrÃculo esquerdo do coraÃÃo, acidente vascular cerebral, infarto do miocÃrdio, morte sÃbita, insuficiÃncias renal e cardÃaca, etc. A hipertensÃo arterial (HTA) ou hipertensÃo arterial sistÃmica (HAS), conhecida popularmente como pressÃo alta, à uma das doenÃas com maior prevalÃncia no mundo moderno. A ECA atua na regulaÃÃo da pressÃo sanguÃnea via conversÃo do decapeptÃdeo angiotensina I no potente vasopressor angiotensina II e tambÃm pela inativaÃÃo da bradicinina, sendo componente central do Sistema Renina-Angiotensina-Aldeosterona (SRAA), que controla a pressÃo sanguÃnea e tem forte influÃncia nas funÃÃes relacionadas ao coraÃÃo e os rins, bem como na contraÃÃo dos vasos sanguÃneos. Nesta tese realiza-se um estudo da bioquÃmica quÃntica de estatinas (atorvastina, rosuvastatina, cerivastatina, mevastatina, sinvastatina e fluvastatina), da aspirina/bromoaspirina e de anti-hipertensivos (captopril, enalapril, lisinopril, ramipril, trandolapril e perindopril) levando-se em conta dados cristalogrÃficos dos seus sÃtios de ligaÃÃo nas proteÃnas HMGR, COX-1 (o da aspirina foi simulado partindo-se dos dados da bromoaspirina) e ECA, respectivamente. As simulaÃÃes computacionais foram realizadas considerando-se a Teoria do Funcional de Densidade (DFT) na aproximaÃÃo da densidade local (LDA) e funcional de troca e correlaÃÃo PWC, com energia de interaÃÃo entre os resÃduos das proteÃnas circunscritos ao sÃtio de ligaÃÃo de raio r e os fÃrmacos calculada atravÃs do mÃtodo de fracionamento molecular com capas conjugadas (MFCC). Os resultados obtidos para as estatinas sugerem que: (i) as mais (menos) eficazes sÃo a atorvastatina e a rosuvastatina (sinvastatina e fluvastatina), o que està de acordo com a clÃnica e valores dos seus Ãndices de concentraÃÃes inibitÃrias IC50; (ii) sÃtios de ligaÃÃo com raios de pelo menos 12 à (alÃm do raio de 9,5 à sugerido pela anÃlise estrita de dados cristalogrÃficos) devem ser considerados para que resÃduos importantes como E665, D767, e R702 sejam considerados para que as eficiÃncias das estatinas sejam corretamente explicadas. Para a aspirina/bromoaspirina utilizou-se um refinamento quÃntico de segunda ordem dos dados cristalogrÃficos para se demonstrar que a energia de ligaÃÃo de ambos com a COX-1 sÃo aproximadamente a mesma, o que explica resultados experimentais de IC50 similares. A existÃncia de resÃduos atrativos e resulsivos à destacada, mostrando-se que Arg120 à o resÃduo que mais atrai o Ãcido salicÃlico apÃs acetilaÃÃo da Ser530, seguido de Ala527, Leu531, Leu359 e Ser353; por outro lado, Glu524 à o resÃduo repulsivo mais efetivo (intensidade comparÃvel ao Arg120), nunca tendo sido antes considerado como resÃduo importante no sÃtio de ligaÃÃo da aspirina/bromoaspirina na COX-1. Finalmente, no caso dos anti-hipertensivos, obtÃm-se que à necessÃrio se considerar raios do sÃtio de ligaÃÃo de 16 à para se obter que o lisinopropil e o ramipril (trandolapril e perindopril) apresentam as maiores (menores) energias de ligaÃÃo, o que explica a maior (menor) constante de inibiÃÃo dos mesmos entre os anti-hipertensivos estudados para a ACE da Drosophila melanogaster.