HIA Report to the Minister for Health on an evaluation and analysis of returns for 1 July 2011 to 30 June 2012 including advice

HIA Report to the Minister for Health The Department of health requested that the Health Insurance Authority provide a report to the Minister ‘in anticipation of the enactment of the health Insurance (Amendment) Bill 2012.” Click here to download PDF 8.87MB The Health Insurance (Amendment) Bill 2012 Link to the Minister’s Second Stage Speech to the Dáil on 14 November 2012          

Acoustic and perceptual analyses of Brazilian male actors' and nonactors' voices: Long-term average spectrum and the Actor's Formant

This study investigates the possible differences between actors' and nonactors' vocal projection strategies using acoustic and perceptual analyses. A total of 11 male actors and 10 male nonactors volunteered as subjects, reading an extended text sample in habitual, moderate, and loud levels. The samples were analyzed for sound pressure level (SPL), alpha ratio (difference between the average SPL of the 1-5 kHz region and the average SPL of the 50 Hz-1 kHz region), fundamental frequency (F0), and long-term average spectrum (LTAS). Through LTAS, the mean frequency of the first formant (171) range, the mean frequency of the actor's formant, the level differences between the F1 frequency region and the F0 region (L1-L0), and the level differences between the strongest peak at 0-1 kHz and that at 3-4 kHz were measured. Eight voice specialists evaluated perceptually the degree of projection, loudness, and tension in the samples. The actors had a greater alpha ratio, stronger level of the actor's formant range, and a higher degree of perceived projection and loudness in all loudness levels. SPL, however, did not differ significantly between the actors and nonactors, and no differences were found in the mean formant frequencies ranges. The alpha ratio and the relative level of the actor's formant range seemed to be related to the degree of perceived loudness. From the physiological point of view, a more favorable glottal setting' providing a higher glottal closing speed, may be characteristic of these actors' projected voices. So, the projected voices, in this group of actors, were more related to the glottic source than to the resonance of the vocal tract.

Differences in Mismatch Negativity (MMN) response to Pure-tone and Speech sounds in normal subjects: an additional explanation

The relation of automatic auditory discrimination, measured with MMN, with the type of stimuli has not been well established in the literature, despite its importance as an electrophysiological measure of central sound representation. In this study, MMN response was elicited by pure-tone and speech binaurally passive auditory oddball paradigm in a group of 8 normal young adult subjects at the same intensity level (75 dB SPL). The frequency difference in pure-tone oddball was 100 Hz (standard = 1 000 Hz; deviant = 1 100 Hz; same duration = 100 ms), in speech oddball (standard /ba/; deviant /pa/; same duration = 175 ms) the Portuguese phonemes are both plosive bi-labial in order to maintain a narrow frequency band. Differences were found across electrode location between speech and pure-tone stimuli. Larger MMN amplitude, duration and higher latency to speech were verified compared to pure-tone in Cz and Fz as well as significance differences in latency and amplitude between mastoids. Results suggest that speech may be processed differently than non-speech; also it may occur in a later stage due to overlapping processes since more neural resources are required to speech processing.

Speech by Mr Micheál Martin TD at Launch of Pre-Registration Nursing Degree Programme

Good afternoon ladies and gentlemen. I am very pleased that you were all able to accept my invitation to join me here today on this landmark occasion for nursing education. It is fitting that all of the key stakeholders from the health and education sectors should be so well represented at the launch of an historic new development. Rapid and unpredictable change throughout society has been the hallmark of the twenty-first century, and healthcare is no exception. Regardless of what change occurs, no one doubts that nursing is intrinsic to the health of this nation. However, significant changes in nurse education are now needed if the profession is to deliver on its social mandate to promote people´s health by providing excellent and sensitive care. As science, technology and the demands of the public for sophisticated and responsive health care become increasingly complex, it is essential that the foundation of nursing education is redesigned. Pre-registration nursing education has already undergone radical change over the past eight years, during which time it has moved from an apprenticeship model of education and training to a diploma based programme firmly rooted in higher education. The Secretary General of my Department, Michael Kelly, played a leading role in bringing about this transformation, which has greatly enhanced the way students are prepared for entry to the nursing profession. The benefits of the revised model of education are clearly evident from the quality of the nurses graduating from the diploma programme. The Commission on Nursing examined the whole area of nursing education, and set out a very convincing case for educating nursing students to degree level. It argued that nurses of the future would be required to possess increased flexibility and the ability to work autonomously. A degree programme would provide nurses with a theoretical underpinning that would enable them to develop their clinical skills to a greater extent and to respond to future challenges in health care, for the benefit of patients and clients of the health services. The Commission has provided a solid framework for the professional development of nurses and midwives, including a process that is already underway for the creation of clinical nurse specialist and advanced nurse practitioner posts. This process will facilitate the transfer of skills across divisions of nursing. In this scenario, it is clearly desirable that the future benchmark qualification for registration as a nurse should be a degree in nursing studies. A Nursing Education Forum was established in early 1999 to prepare a strategic framework for the implementation of a nursing degree programme. When launching the Forum´s report last January, I indicated that the Government had agreed in principle to the introduction of the proposed degree programme next year. At the time two substantial outstanding issues had yet to be resolved, namely the basis on which nurse teachers would transfer from the health sector to the education sector and the amount of capital and revenue funding required to operate the degree programme. My Department has brokered agreements between the Nursing Alliance and the Higher Education Institutions for the assimilation of nurse teachers as lecturers into their affiliated institutions. The terms of these agreements have been accepted by all four nursing unions following a ballot of their nurse teacher members. I would like to pay particular tribute to all nurse teachers who have contributed to shaping the position, relevance and visibility of nursing through leadership, which embodies scholarship and excellence in the profession of nursing itself. In response to a recommendation of the Nursing Education Forum, I established an Inter-Departmental Steering Committee, chaired by Bernard Carey of my Department, to consider all the funding and policy issues. This Steering Committee includes representatives of the Department of Finance and the Department of Education and Science as well as the Higher Education Authority. The Steering Committee has been engaged in intensive negotiations with representatives of the Conference of Heads of Irish Universities and the Institutes of Technology in relation to their capital and revenue funding requirements. These negotiations were successfully concluded within the past few weeks. The satisfactory resolution of the industrial relations and funding issues cleared the way for me to go to the Government with concrete proposals for the implementation of degree level education for nursing students. I am delighted to announce here today that the Government has approved all of my proposals, and that a four-year undergraduate pre-registration nursing degree programme will be implemented on a nation-wide basis at the start of the next academic year, 2002/2003. The Government has approved the provision of capital funding totalling £176 million pounds for a major building and equipment programme to facilitate the full integration of nursing students into the higher education sector. This programme is due to be completed by September 2004, and will ensure that nursing students are accommodated in purpose built schools of nursing studies with state of the art clinical skills and human science laboratories at thirteen higher education sites throughout the country. The Government has also agreed to make available the substantial additional revenue funding required to support the nursing degree programme. By 2006, the full year cost of operating the programme will rise to some £43 million pounds. The scale of this investment in pre-registration nursing education is enormous by any yardstick. It demonstrates the firm commitment of myself and my Government colleagues to the full implementation of the recommendations of the Commission on Nursing, of which the introduction of pre-registration degree level education is arguably the most important. This historic decision, and it is truly historic, will finally put the education of nurses on a par with the education of other health care professionals. The nursing profession has long been striving for parity, and my own involvement in the achievement of it is a matter of deep personal satisfaction to me. I am also pleased to announce that the Government has approved my plans for increasing the number of nursing training places to coincide with the implementation of the degree programme next year. Ninety-three additional places in mental handicap and psychiatric nursing will be created at Athlone, Letterkenny, Tralee and Waterford Institutes of Technology. This will yield 392 extra places over the four years of the degree programme. A total of 1,640 places annually on the new degree programme will thus be available. This is an all-time record, and maintaining the annual student intake at this level for the foreseeable future is a key element of my overall strategy for ensuring that we produce sufficient “home-grown” nurses for our health services. I am aware that the Nursing Alliance were anxious that some funding would be provided for the further academic career development of nurse teachers who transfer to one of the six Universities that will be involved in the delivery of the degree programme. I am happy to confirm that up to £300,000 in total per year will be available for this purpose over the first four years of the degree programme. In line with a recommendation of the Commission on Nursing, my Department will have responsibility for the administration of the nursing degree budget until the programme has been bedded down in the higher education sector. A primary concern will be to ensure that the substantial capital and revenue funding involved is ring-fenced for nursing studies. It is intended that responsibility for the budget will be transferred to the Department of Education and Science after the first cohort of nursing degree students have graduated in 2006. In the context of today´s launch, it is relevant to refer to a special initiative that I introduced last year to assist registered nurses wishing to undertake part-time nursing degree courses. Under this initiative, nurses are entitled to have their course fees paid by their employers in return for a commitment to continue working in the public health service for a period following completion of the course. This initiative has proved extremely popular with large numbers of nurses availing of it. I want to confirm here today that the free fees initiative will continue in operation until 2005, at a total cost of at least £15 million pounds. I am giving this commitment in order to assure this year´s intake of nursing students to the final diploma programmes that fee support for a part-time nursing degree course will be available to them when they graduate in three years time. The focus of today´s celebration is rightly on the landmark Government decision to implement the nursing degree programme next year. As Minister for Health and Children, and as a former Minister for Education, I also have a particular interest in the educational opportunities available to other health service workers to upgrade their skills. I am pleased to announce that the Government has approved my proposals for the introduction of a sponsorship scheme for suitable, experienced health care assistants who wish to become nurses. This new scheme will commence next year and will be administered by the health boards. Successful applicants will be allowed to retain their existing salaries throughout the four years of the degree programme in return for a commitment to work as nurses for their health service employer for a period of five years following registration. Up to forty sponsorships will be available annually. The new scheme will enable suitable applicants to undertake nursing education and training without suffering financial hardship. The greatest advantage of the scheme will be the retention by the public health service of staff who are supported under it, since they will have had practical experience of working in the service and their own personal commitment to upgrading their skills will be informed by that experience. I am confident that the sponsorship scheme will be warmly welcomed by health service unions representing care assistants as providing an exciting new career development path for their members. Education and health are now the two pillars upon which the profession of nursing rests. We must continue to build bridges, even tunnels where needed to strengthen this partnership. We must all understand partnerships donâ?Tt just happen they are designed and must be worked at. The changes outlined here today are powerful incentives for those in healthcare agencies, academic institutions and regulatory bodies to design revolutionary programmes capable of shaping a critical mass of excellent practitioners. You have an opportunity, greater perhaps than has been granted to any other generation in history to make certain those changes are for the good. Ultimately changes that will make the country a healthier and more equitable place to live. The challenge relates to building a seamless preparatory programme which equally respects both education and practise as an indivisible duo whilst ensuring that high tech does not replace the human touch. This is a special day in the history of the development of the Irish nursing profession, and I would like to thank everybody for their contribution. I want to express my particular appreciation of two people who by this stage are well known to all of you – Bernard Carey of my Department and Siobhán O´Halloran of the National Implementation Committee. Bernard and Siobhán have devoted considerable time and energy to the project on my behalf over the past fourteen months or so. That we are here today celebrating the launch of degree level education is due in no small part to their successful execution of the mandate that I gave them. We live in a rapidly changing world, one in which nursing can no longer rely on systems of the past to guide it through the new millennium. In terms of contemporary healthcare, nursing is no longer just a reciprocal kindness but rather a highly complex set of professional behaviours, which require serious educational investment. Pre-registration nurse education will always need development and redesign to ensure our health care system meets the demands of modern society. Nothing is finite. Today more than ever the health system is dependent on the resourcefulness of nursing. I have no doubt that the new educational landscape painted will ensure that nurses of the future will be increasingly innovative, independent and in demand. The unmistakable message from my Department is that nursing really matters. Thank you.

Healthy child, healthy future: speech and language therapy for children

This resource is designed to reinforce a collaborative approach between speech and language therapists, referrers and parents in the identification and management of children with developmental speech and language and communication needs (including children with feeding and/or swallowing difficulties). It includes a comprehensive key skills section, which provides details on the communication-related skills a child should have acquired at each stage in his/her early years development. It also includes specific criteria and guidelines for referral, should there be concern about whether the child has a significant problem. The resource provides additional guidance on: • communication and child play; • speech sound development; • dummies; • stammering; • dysphonia; • bilingualism; • feeding and swallowing difficulties. Lists of supplementary leaflets, handouts and websites, as well as a bibliography, are also included.

PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

Speech therapy after stroke: trial shows only that practice varies

Bowen and colleagues’ methods and conclusions raise concerns.1 At best, the trial evaluates the variability in current practice. In no way is it a robust test of treatment. Two communication impairments (aphasia and dysarthria) were included. In the post-acute stage spontaneous recovery is highly unpredictable, and changes in the profile of impairment during this time are common.2 Both impairments manifest in different forms,3 which may be more or less responsive to treatment. A third kind of impairment, apraxia of speech, was not excluded but was not targeted in therapy. All three impairments can and do co-occur. Whether randomised controlled trial designs can effectively cope with such complex disorders has been discussed elsewhere.4 Treatment was defined within terms of current practice but was unconstrained. Therefore, the treatment group would have received a variety of therapeutic approaches and protocols, some of which may indeed be ineffective. Only 53% of the contact time with a speech and language therapist was direct (one to one), the rest was impairment based therapy. In contrast, all of the visitors’ time was direct contact, usually in conversation. In both groups, the frequency and length of contact time varied. We already know that the transfer from impairment based therapy to functional communication can be limited and varies across individuals.5 However, it is not possible to conclude from this trial that one to one impairment based therapy should be replaced. For that, a well defined impairment therapy protocol must be directly compared with a similarly well defined functional communication therapy, with an attention control.

Corpus-Based Speech Enhancement With Uncertainty Modeling and Cepstral Smoothing

We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve the sound of speech signals in background noise. The proposed new method modifies Xiao's method in four significant ways. Firstly, it employs a Gaussian mixture model (GMM) instead of a vector quantizer in the phoneme recognition front-end. Secondly, the state decoding of the recognition stage is supported with an uncertainty modeling technique. With the GMM and the uncertainty modeling it is possible to eliminate the need for noise dependent system training. Thirdly, the post-processing of the original method via sinusoidal modeling is replaced with a powerful cepstral smoothing operation. And lastly, due to the improvements of these modifications, it is possible to extend the operational bandwidth of the procedure from 4 kHz to 8 kHz. The performance of the proposed method was evaluated across different noise types and different signal-to-noise ratios. The new method was able to significantly outperform traditional methods, including the one by Xiao and Nickel, in terms of PESQ scores and other objective quality measures. Results of subjective CMOS tests over a smaller set of test samples support our claims.

Differentiation in Male and Female Speech Styles

From the moment of their birth, a person's life is determined by their sex. Ms. Goroshko wants to know why this difference is so striking, why society is so concerned to sustain it, and how it is able to persist even when certain national or behavioural stereotypes are erased between people. She is convinced of the existence of not only social, but biological differences between men and women, and set herself the task, in a manuscript totalling 126 pages, written in Ukrainian and including extensive illustrations, of analysing these distinctions as they are manifested in language. She points out that, even before 1900, certain stylistic differences between the ways that men and women speak had been noted. Since then it has become possible, for instance in the case of Japanese, to point to examples of male and female sub-languages. In general, one can single out the following characteristics. Males tend to write with less fluency, to refer to events in a verb-phrase, to be time-oriented, to involve themselves more in their references to events, to locate events in their personal sphere of activity, and to refer less to others. Therefore, concludes Ms Goroshko, the male is shown to be more active, more ego-involved in what he does, and less concerned about others. Women, in contrast, were more fluent, referred to events in a noun-phrase, were less time-oriented, tended to be less involved in their event-references, locate events within their interactive community and refer more to others. They spent much more time discussing personal and domestic subjects, relationship problems, family, health and reproductive matters, weight, food and clothing, men, and other women. As regards discourse strategies, Ms Goroshko notes the following. Men more often begin a conversation, they make more utterances, these utterances are longer, they make more assertions, speak less carefully, generally determine the topic of conversation, speak more impersonally, use more vulgar expressions, and use fewer diminutives and more imperatives. Women's speech strategies, apart from being the opposite of those enumerated above, also contain more euphemisms, polite forms, apologies, laughter and crying. All of the above leads Ms. Goroshko to conclude that the differences between male and female speech forms are more striking than the similarities. Furthermore she is convinced that the biological divergence between the sexes is what generates the verbal divergence, and that social factors can only intensify or diminish the differentiation in verbal behaviour established by the sex of a person. Bearing all this in mind, Ms Goroshko set out to construct a grammar of male and female styles of speaking within Russian. One of her most important research tools was a certain type of free association test. She took a list comprising twelve stimuli (to love, to have, to speak, to fuck, a man, a woman, a child, the sky, a prayer, green, beautiful) and gave it to a group of participants specially selected, according to a preliminary psychological testing, for the high levels of masculinity or femininity they displayed. Preliminary responses revealed that the female reactions were more diverse than the male ones, there were more sentences and word combinations in the female reactions, men gave more negative responses to the stimulus and sometimes didn't want to react at all, women reacted more to adjectives and men to nouns, and that, surprisingly, women coloured more negatively their reactions to the words man, to love and a child (Ms. Goroshko is inclined to attribute this to the present economic situation in Russia). Another test performed by Ms. Goroshko was the so-called "defective text" developed by A.A. Brudny. All participants were distributed with packets of complete sentences, which had been taken from a text and then mixed at random. The task was to reconstruct the original text. There were three types of test, the first descriptive, the second narrative, and the third logical. Ms. Goroshko created computer programmes to analyse the results. She found that none of the reconstructed texts was coincident with the original, differing both from the original text and amongst themselves and that there were many more disparities in the male than the female texts. In the descriptive and logical texts the differences manifested themselves more clearly in the male texts, and in the narrative texts in the female texts. The widest dispersal of values was observed at the outset, while the female text ending was practically coincident with the original (in contrast to the male ending). The greatest differences in text reconstruction for both males and females were registered in the middle of the texts. Women, Ms. Goroshko claims, were more sensitive to the semantic structure of the texts, since they assembled the narrative text much more accurately than the other two, while the men assembled more accurately the logical text. Texts written by women were assembled more accurately by women and texts by men by men. On the basis of computer analysis, Ms. Goroshko found that female speech was substantially more emotional. It was expressed by various means, hyperbole, metaphor, comparisons, epithets, ways of enumeration, and with the aid of interjections, rhetorical questions, exclamations. The level of literacy was higher for female speech, and there were fewer mistakes in grammar and spelling in female texts. The last stage of Ms Goroshko's research concerned the social stereotypes of beliefs about men and women in Russian society today. A large number of respondents were asked questions such as "What merits must a woman possess?", "What are male vices and virtues?", etc. After statistical manipulation, an image of modern man and woman, as it exists in the minds of modern Russian men and women, emerged. Ms. Goroshko believes that her findings are significant not only within the field of linguistics. She has already successfully worked on anonymous texts and been able to decide on the sex of the author and consequently believes that in the future her research may even be of benefit to forensic science.

Speech outcome in complete unilateral cleft lip and palate - a comparison of three methods of the hard palate closure.

The aim of this study was to compare the speech in subjects with cleft lip and palate, in whom three methods of the hard palate closure were used. One hundred and thirty-seven children (96 boys, 41 girls; mean age = 12 years, SD = 1·2) with complete unilateral cleft lip and palate (CUCLP) operated by a single surgeon with a one-stage method were evaluated. The management of the cleft lip and soft palate was comparable in all subjects; for hard palate repair, three different methods were used: bilateral von Langenbeck closure (b-vL group, n = 39), unilateral von Langenbeck closure (u-vL group, n = 56) and vomerplasty (v-p group, n = 42). Speech was assessed: (i) perceptually for the presence of a) hypernasality, b) compensatory articulations (CAs), c) audible nasal air emissions (ANE) and d) speech intelligibility; (ii) for the presence of compensatory facial grimacing, (iii) with clinical intra-oral evaluation and (iv) with videonasendoscopy. A total rate of hypernasality requiring pharyngoplasty was 5·1%; total incidence post-oral compensatory articulations (CAs) was 2·2%. The overall speech intelligibility was good in 84·7% of cases. Oronasal fistulas (ONFs) occurred in 15·7% b-vL subjects, 7·1% u-vL subjects and 50% v-p subjects (P < 0·001). No statistically significant intergroup differences for hypernasality, CAs and intelligibility were found (P > 0·1). In conclusion, the speech after early one-stage repair of CUCLP was satisfactory. The method of hard palate repair affected the incidence of ONFs, which, however, caused relatively mild and inconsistent speech errors.

Contributions to Speech Analytics based on Speech Recognition and Topic Identification

La última década ha sido testigo de importantes avances en el campo de la tecnología de reconocimiento de voz. Los sistemas comerciales existentes actualmente poseen la capacidad de reconocer habla continua de múltiples locutores, consiguiendo valores aceptables de error, y sin la necesidad de realizar procedimientos explícitos de adaptación. A pesar del buen momento que vive esta tecnología, el reconocimiento de voz dista de ser un problema resuelto. La mayoría de estos sistemas de reconocimiento se ajustan a dominios particulares y su eficacia depende de manera significativa, entre otros muchos aspectos, de la similitud que exista entre el modelo de lenguaje utilizado y la tarea específica para la cual se está empleando. Esta dependencia cobra aún más importancia en aquellos escenarios en los cuales las propiedades estadísticas del lenguaje varían a lo largo del tiempo, como por ejemplo, en dominios de aplicación que involucren habla espontánea y múltiples temáticas. En los últimos años se ha evidenciado un constante esfuerzo por mejorar los sistemas de reconocimiento para tales dominios. Esto se ha hecho, entre otros muchos enfoques, a través de técnicas automáticas de adaptación. Estas técnicas son aplicadas a sistemas ya existentes, dado que exportar el sistema a una nueva tarea o dominio puede requerir tiempo a la vez que resultar costoso. Las técnicas de adaptación requieren fuentes adicionales de información, y en este sentido, el lenguaje hablado puede aportar algunas de ellas. El habla no sólo transmite un mensaje, también transmite información acerca del contexto en el cual se desarrolla la comunicación hablada (e.g. acerca del tema sobre el cual se está hablando). Por tanto, cuando nos comunicamos a través del habla, es posible identificar los elementos del lenguaje que caracterizan el contexto, y al mismo tiempo, rastrear los cambios que ocurren en estos elementos a lo largo del tiempo. Esta información podría ser capturada y aprovechada por medio de técnicas de recuperación de información (information retrieval) y de aprendizaje de máquina (machine learning). Esto podría permitirnos, dentro del desarrollo de mejores sistemas automáticos de reconocimiento de voz, mejorar la adaptación de modelos del lenguaje a las condiciones del contexto, y por tanto, robustecer al sistema de reconocimiento en dominios con condiciones variables (tales como variaciones potenciales en el vocabulario, el estilo y la temática). En este sentido, la principal contribución de esta Tesis es la propuesta y evaluación de un marco de contextualización motivado por el análisis temático y basado en la adaptación dinámica y no supervisada de modelos de lenguaje para el robustecimiento de un sistema automático de reconocimiento de voz. Esta adaptación toma como base distintos enfoque de los sistemas mencionados (de recuperación de información y aprendizaje de máquina) mediante los cuales buscamos identificar las temáticas sobre las cuales se está hablando en una grabación de audio. Dicha identificación, por lo tanto, permite realizar una adaptación del modelo de lenguaje de acuerdo a las condiciones del contexto. El marco de contextualización propuesto se puede dividir en dos sistemas principales: un sistema de identificación de temática y un sistema de adaptación dinámica de modelos de lenguaje. Esta Tesis puede describirse en detalle desde la perspectiva de las contribuciones particulares realizadas en cada uno de los campos que componen el marco propuesto: _ En lo referente al sistema de identificación de temática, nos hemos enfocado en aportar mejoras a las técnicas de pre-procesamiento de documentos, asimismo en contribuir a la definición de criterios más robustos para la selección de index-terms. – La eficiencia de los sistemas basados tanto en técnicas de recuperación de información como en técnicas de aprendizaje de máquina, y específicamente de aquellos sistemas que particularizan en la tarea de identificación de temática, depende, en gran medida, de los mecanismos de preprocesamiento que se aplican a los documentos. Entre las múltiples operaciones que hacen parte de un esquema de preprocesamiento, la selección adecuada de los términos de indexado (index-terms) es crucial para establecer relaciones semánticas y conceptuales entre los términos y los documentos. Este proceso también puede verse afectado, o bien por una mala elección de stopwords, o bien por la falta de precisión en la definición de reglas de lematización. En este sentido, en este trabajo comparamos y evaluamos diferentes criterios para el preprocesamiento de los documentos, así como también distintas estrategias para la selección de los index-terms. Esto nos permite no sólo reducir el tamaño de la estructura de indexación, sino también mejorar el proceso de identificación de temática. – Uno de los aspectos más importantes en cuanto al rendimiento de los sistemas de identificación de temática es la asignación de diferentes pesos a los términos de acuerdo a su contribución al contenido del documento. En este trabajo evaluamos y proponemos enfoques alternativos a los esquemas tradicionales de ponderado de términos (tales como tf-idf ) que nos permitan mejorar la especificidad de los términos, así como también discriminar mejor las temáticas de los documentos. _ Respecto a la adaptación dinámica de modelos de lenguaje, hemos dividimos el proceso de contextualización en varios pasos. – Para la generación de modelos de lenguaje basados en temática, proponemos dos tipos de enfoques: un enfoque supervisado y un enfoque no supervisado. En el primero de ellos nos basamos en las etiquetas de temática que originalmente acompañan a los documentos del corpus que empleamos. A partir de estas, agrupamos los documentos que forman parte de la misma temática y generamos modelos de lenguaje a partir de dichos grupos. Sin embargo, uno de los objetivos que se persigue en esta Tesis es evaluar si el uso de estas etiquetas para la generación de modelos es óptimo en términos del rendimiento del reconocedor. Por esta razón, nosotros proponemos un segundo enfoque, un enfoque no supervisado, en el cual el objetivo es agrupar, automáticamente, los documentos en clusters temáticos, basándonos en la similaridad semántica existente entre los documentos. Por medio de enfoques de agrupamiento conseguimos mejorar la cohesión conceptual y semántica en cada uno de los clusters, lo que a su vez nos permitió refinar los modelos de lenguaje basados en temática y mejorar el rendimiento del sistema de reconocimiento. – Desarrollamos diversas estrategias para generar un modelo de lenguaje dependiente del contexto. Nuestro objetivo es que este modelo refleje el contexto semántico del habla, i.e. las temáticas más relevantes que se están discutiendo. Este modelo es generado por medio de la interpolación lineal entre aquellos modelos de lenguaje basados en temática que estén relacionados con las temáticas más relevantes. La estimación de los pesos de interpolación está basada principalmente en el resultado del proceso de identificación de temática. – Finalmente, proponemos una metodología para la adaptación dinámica de un modelo de lenguaje general. El proceso de adaptación tiene en cuenta no sólo al modelo dependiente del contexto sino también a la información entregada por el proceso de identificación de temática. El esquema usado para la adaptación es una interpolación lineal entre el modelo general y el modelo dependiente de contexto. Estudiamos también diferentes enfoques para determinar los pesos de interpolación entre ambos modelos. Una vez definida la base teórica de nuestro marco de contextualización, proponemos su aplicación dentro de un sistema automático de reconocimiento de voz. Para esto, nos enfocamos en dos aspectos: la contextualización de los modelos de lenguaje empleados por el sistema y la incorporación de información semántica en el proceso de adaptación basado en temática. En esta Tesis proponemos un marco experimental basado en una arquitectura de reconocimiento en ‘dos etapas’. En la primera etapa, empleamos sistemas basados en técnicas de recuperación de información y aprendizaje de máquina para identificar las temáticas sobre las cuales se habla en una transcripción de un segmento de audio. Esta transcripción es generada por el sistema de reconocimiento empleando un modelo de lenguaje general. De acuerdo con la relevancia de las temáticas que han sido identificadas, se lleva a cabo la adaptación dinámica del modelo de lenguaje. En la segunda etapa de la arquitectura de reconocimiento, usamos este modelo adaptado para realizar de nuevo el reconocimiento del segmento de audio. Para determinar los beneficios del marco de trabajo propuesto, llevamos a cabo la evaluación de cada uno de los sistemas principales previamente mencionados. Esta evaluación es realizada sobre discursos en el dominio de la política usando la base de datos EPPS (European Parliamentary Plenary Sessions - Sesiones Plenarias del Parlamento Europeo) del proyecto europeo TC-STAR. Analizamos distintas métricas acerca del rendimiento de los sistemas y evaluamos las mejoras propuestas con respecto a los sistemas de referencia. ABSTRACT The last decade has witnessed major advances in speech recognition technology. Today’s commercial systems are able to recognize continuous speech from numerous speakers, with acceptable levels of error and without the need for an explicit adaptation procedure. Despite this progress, speech recognition is far from being a solved problem. Most of these systems are adjusted to a particular domain and their efficacy depends significantly, among many other aspects, on the similarity between the language model used and the task that is being addressed. This dependence is even more important in scenarios where the statistical properties of the language fluctuates throughout the time, for example, in application domains involving spontaneous and multitopic speech. Over the last years there has been an increasing effort in enhancing the speech recognition systems for such domains. This has been done, among other approaches, by means of techniques of automatic adaptation. These techniques are applied to the existing systems, specially since exporting the system to a new task or domain may be both time-consuming and expensive. Adaptation techniques require additional sources of information, and the spoken language could provide some of them. It must be considered that speech not only conveys a message, it also provides information on the context in which the spoken communication takes place (e.g. on the subject on which it is being talked about). Therefore, when we communicate through speech, it could be feasible to identify the elements of the language that characterize the context, and at the same time, to track the changes that occur in those elements over time. This information can be extracted and exploited through techniques of information retrieval and machine learning. This allows us, within the development of more robust speech recognition systems, to enhance the adaptation of language models to the conditions of the context, thus strengthening the recognition system for domains under changing conditions (such as potential variations in vocabulary, style and topic). In this sense, the main contribution of this Thesis is the proposal and evaluation of a framework of topic-motivated contextualization based on the dynamic and non-supervised adaptation of language models for the enhancement of an automatic speech recognition system. This adaptation is based on an combined approach (from the perspective of both information retrieval and machine learning fields) whereby we identify the topics that are being discussed in an audio recording. The topic identification, therefore, enables the system to perform an adaptation of the language model according to the contextual conditions. The proposed framework can be divided in two major systems: a topic identification system and a dynamic language model adaptation system. This Thesis can be outlined from the perspective of the particular contributions made in each of the fields that composes the proposed framework: _ Regarding the topic identification system, we have focused on the enhancement of the document preprocessing techniques in addition to contributing in the definition of more robust criteria for the selection of index-terms. – Within both information retrieval and machine learning based approaches, the efficiency of topic identification systems, depends, to a large extent, on the mechanisms of preprocessing applied to the documents. Among the many operations that encloses the preprocessing procedures, an adequate selection of index-terms is critical to establish conceptual and semantic relationships between terms and documents. This process might also be weakened by a poor choice of stopwords or lack of precision in defining stemming rules. In this regard we compare and evaluate different criteria for preprocessing the documents, as well as for improving the selection of the index-terms. This allows us to not only reduce the size of the indexing structure but also to strengthen the topic identification process. – One of the most crucial aspects, in relation to the performance of topic identification systems, is to assign different weights to different terms depending on their contribution to the content of the document. In this sense we evaluate and propose alternative approaches to traditional weighting schemes (such as tf-idf ) that allow us to improve the specificity of terms, and to better identify the topics that are related to documents. _ Regarding the dynamic language model adaptation, we divide the contextualization process into different steps. – We propose supervised and unsupervised approaches for the generation of topic-based language models. The first of them is intended to generate topic-based language models by grouping the documents, in the training set, according to the original topic labels of the corpus. Nevertheless, a goal of this Thesis is to evaluate whether or not the use of these labels to generate language models is optimal in terms of recognition accuracy. For this reason, we propose a second approach, an unsupervised one, in which the objective is to group the data in the training set into automatic topic clusters based on the semantic similarity between the documents. By means of clustering approaches we expect to obtain a more cohesive association of the documents that are related by similar concepts, thus improving the coverage of the topic-based language models and enhancing the performance of the recognition system. – We develop various strategies in order to create a context-dependent language model. Our aim is that this model reflects the semantic context of the current utterance, i.e. the most relevant topics that are being discussed. This model is generated by means of a linear interpolation between the topic-based language models related to the most relevant topics. The estimation of the interpolation weights is based mainly on the outcome of the topic identification process. – Finally, we propose a methodology for the dynamic adaptation of a background language model. The adaptation process takes into account the context-dependent model as well as the information provided by the topic identification process. The scheme used for the adaptation is a linear interpolation between the background model and the context-dependent one. We also study different approaches to determine the interpolation weights used in this adaptation scheme. Once we defined the basis of our topic-motivated contextualization framework, we propose its application into an automatic speech recognition system. We focus on two aspects: the contextualization of the language models used by the system, and the incorporation of semantic-related information into a topic-based adaptation process. To achieve this, we propose an experimental framework based in ‘a two stages’ recognition architecture. In the first stage of the architecture, Information Retrieval and Machine Learning techniques are used to identify the topics in a transcription of an audio segment. This transcription is generated by the recognition system using a background language model. According to the confidence on the topics that have been identified, the dynamic language model adaptation is carried out. In the second stage of the recognition architecture, an adapted language model is used to re-decode the utterance. To test the benefits of the proposed framework, we carry out the evaluation of each of the major systems aforementioned. The evaluation is conducted on speeches of political domain using the EPPS (European Parliamentary Plenary Sessions) database from the European TC-STAR project. We analyse several performance metrics that allow us to compare the improvements of the proposed systems against the baseline ones.

Speech and non-speech stimuli in the prediction of early reading skills:the influence of processing demands and response-type

Purpose: Both phonological (speech) and auditory (non-speech) stimuli have been shown to predict early reading skills. However, previous studies have failed to control for the level of processing required by tasks administered across the two levels of stimuli. For example, phonological tasks typically tap explicit awareness e.g., phoneme deletion, while auditory tasks usually measure implicit awareness e.g., frequency discrimination. Therefore, the stronger predictive power of speech tasks may be due to their higher processing demands, rather than the nature of the stimuli. Method: The present study uses novel tasks that control for level of processing (isolation, repetition and deletion) across speech (phonemes and nonwords) and non-speech (tones) stimuli. 800 beginning readers at the onset of literacy tuition (mean age 4 years and 7 months) were assessed on the above tasks as well as word reading and letter-knowledge in the first part of a three time-point longitudinal study. Results: Time 1 results reveal a significantly higher association between letter-sound knowledge and all of the speech compared to non-speech tasks. Performance was better for phoneme than tone stimuli, and worse for deletion than isolation and repetition across all stimuli. Conclusions: Results are consistent with phonological accounts of reading and suggest that level of processing required by the task is less important than stimuli type in predicting the earliest stage of reading.

Segmentation of a Speech Signal with Application of Fast Wavelet Transformation

The article describes the method of preliminary segmentation of a speech signal with wavelet transformation use, consisting of two stages. At the first stage there is an allocation of sibilants and pauses, at the second – the further segmentation of the rest signal parts.

Nebivolol Reduces Central Blood Pressure In Stage I Hypertensive Patients: Experimental Single Cohort Study.

Assessment of central blood pressure (BP) has grown substantially over recent years because evidence has shown that central BP is more relevant to cardiovascular outcomes than peripheral BP. Thus, different classes of antihypertensive drugs have different effects on central BP despite similar reductions in brachial BP. The aim of this study was to investigate the effect of nebivolol, a β-blocker with vasodilator properties, on the biochemical and hemodynamic parameters of hypertensive patients. Experimental single cohort study conducted in the outpatient clinic of a university hospital. Twenty-six patients were recruited. All of them underwent biochemical and hemodynamic evaluation (BP, heart rate (HR), central BP and augmentation index) before and after 3 months of using nebivolol. 88.5% of the patients were male; their mean age was 49.7 ± 9.3 years and most of them were overweight (29.6 ± 3.1 kg/m2) with large abdominal waist (102.1 ± 7.2 cm). There were significant decreases in peripheral systolic BP (P = 0.0020), diastolic BP (P = 0.0049), HR (P < 0.0001) and central BP (129.9 ± 12.3 versus 122.3 ± 10.3 mmHg; P = 0.0083) after treatment, in comparison with the baseline values. There was no statistical difference in the augmentation index or in the biochemical parameters, from before to after the treatment. Nebivolol use seems to be associated with significant reduction of central BP in stage I hypertensive patients, in addition to reductions in brachial systolic and diastolic BP.

Influence Of The Stage Of Ripeness On The Composition Of Iridoids And Phenolic Compounds In Genipap (genipa Americana L.).

Genipap fruits, native to the Amazon region, were classified in relation to their stage of ripeness according to firmness and peel color. The influence of the part of the genipap fruit and ripeness stage on the iridoid and phenolic compound profiles was evaluated by HPLC-DAD-MS(n), and a total of 17 compounds were identified. Geniposide was the major compound in both parts of the unripe genipap fruits, representing >70% of the total iridoids, whereas 5-caffeoylquinic acid was the major phenolic compound. In ripe fruits, genipin gentiobioside was the major compound in the endocarp (38%) and no phenolic compounds were detected. During ripening, the total iridoid content decreased by >90%, which could explain the absence of blue pigment formation in the ripe fruits after their injury. This is the first time that the phenolic compound composition and iridoid contents of genipap fruits have been reported in the literature.