Automated Transcription System for Malayalam Language

Malayalam is one of the 22 scheduled languages in India with more than 130 million speakers. This paper presents a report on the development of a speaker independent, continuous transcription system for Malayalam. The system employs Hidden Markov Model (HMM) for acoustic modeling and Mel Frequency Cepstral Coefficient (MFCC) for feature extraction. It is trained with 21 male and female speakers in the age group ranging from 20 to 40 years. The system obtained a word recognition accuracy of 87.4% and a sentence recognition accuracy of 84%, when tested with a set of continuous speech data.

Malayalam Isolated Digit Recognition using HMM and PLP cepstral coefficient

Development of Malayalam speech recognition system is in its infancy stage; although many works have been done in other Indian languages. In this paper we present the first work on speaker independent Malayalam isolated speech recognizer based on PLP (Perceptual Linear Predictive) Cepstral Coefficient and Hidden Markov Model (HMM). The performance of the developed system has been evaluated with different number of states of HMM (Hidden Markov Model). The system is trained with 21 male and female speakers in the age group ranging from 19 to 41 years. The system obtained an accuracy of 99.5% with the unseen data

Connected digit speech recognition system for Malayalam language

A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer forMalayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization and continuous density Hidden Markov Model (HMM) in the recognition process. Viterbi algorithm is used for decoding. The training data base has the utterance of 21 speakers from the age group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker is asked to read 20 set of continuous digits. The system obtained an accuracy of 99.5 % with the unseen data.

A Comparative study of HMM and SVM in Malayalam Digit Recognition

A primary medium for the human beings to communicate through language is Speech. Automatic Speech Recognition is wide spread today. Recognizing single digits is vital to a number of applications such as voice dialling of telephone numbers, automatic data entry, credit card entry, PIN (personal identification number) entry, entry of access codes for transactions, etc. In this paper we present a comparative study of SVM (Support Vector Machine) and HMM (Hidden Markov Model) to recognize and identify the digits used in Malayalam speech.

Modeling Stock Order Flows and Learning Market-Making from Data

Stock markets employ specialized traders, market-makers, designed to provide liquidity and volume to the market by constantly supplying both supply and demand. In this paper, we demonstrate a novel method for modeling the market as a dynamic system and a reinforcement learning algorithm that learns profitable market-making strategies when run on this model. The sequence of buys and sells for a particular stock, the order flow, we model as an Input-Output Hidden Markov Model fit to historical data. When combined with the dynamics of the order book, this creates a highly non-linear and difficult dynamic system. Our reinforcement learning algorithm, based on likelihood ratios, is run on this partially-observable environment. We demonstrate learning results for two separate real stocks.

Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence

Diseño de una vía clínica para la vigilancia de hepatocarcinoma y evaluación económica

El carcinoma Hepatocelular (HCC) representa la sexta causa más frecuente de cáncer, y la tercera causa de muerte relacionada con cáncer en el mundo con aproximadamente 600.000 muertes anuales. En el 70 % de los casos, este se desarrolla en presencia de una enfermedad crónica del hígado como la cirrosis u otras enfermedades inflamatorias, por lo que practicar métodos de tamizaje para su diagnóstico precoz, pudieran establecer un mejor pronóstico. El objetivo de este trabajo es diseñar una vía clínica capaz de homogenizar el proceso de tamizaje de HCC, soportando su realización con la realización de una evaluación económica de esta intervención. Se realiza una búsqueda sistemática de literatura y se propone una vía clínica para la vigilancia de HCC en Colombia. A esta propuesta se aplica una evaluación económica tipo costo-efectividad mediante un modelo de Markov de la intervención propuesta, comparando la aplicación de la vía clínica propuesta frente al manejo actual en 100 pacientes considerados con riesgo (cirrosis, portadores de HBV y/o portadores de HCV) con un horizonte de tiempo de 30 años analizando como desenlace los años de vida salvados (LYS) desde la perspectiva del tercero pagador para Colombia a precios de 2009. El análisis determina una disminución de la mortalidad en un 40%, y un valor ICER de US$ 1,438 por LYS, por lo cual se concluye que resulta costo efectivo la aplicación de esta propuesta de tamizaje. Es necesario realizar una prueba para la aplicación de la vía clínica.

Estudio Costo-Efectividad de Lidocaína tópica como adyuvante a Pregabalina y Gabapentina en dolor neuropático periférico en una I.P.S de Bogotá 2011.

Introducción: el dolor neuropático es una patología de considerable prevalencia e impacto socio-económico en la población latinoamericana, la evidencia clínica sugiere que los ligandos de canales de calcio y el parche de Lidocaína pueden tratar exitosamente el dolor neuropático periférico y localizado. Metodología: se realizo una evaluación económica tipo costo-efectividad, observacional y retrospectiva con datos extraídos de las historias clínicas de pacientes atendidos en la clínica de dolor de la IPS. La variable primaria de efectividad fue la mejoría del dolor medida mediante escala visual análoga. Resultados: se estudiaron 94 pacientes tratados con: Gabapentina (G) 21, Pregabalina (P) 24, Gabapentina+ lidocaína (G/P) 24, Pregabalina + Lidocaína (P/L) 25, los costos asociados al tratamiento son los siguientes COP$114.070.835, COP$105.855.920, COP$88.717.481 COP$89.854.712 respectivamente, el número de pacientes con mejoría significativa de dolor fue: 8,10,9 y 21 pacientes respectivamente. El ICER de G/L con respecto a G fue: COP$ -25.353.354. El ICER de P/L con respecto a P fue: COP$ -1.454.655. Conclusiones: la adición del parche de lidocaína a la terapia regular con P/L represento una disminución de consumo de recursos en salud como uso de medicamentos co-analgésicos, analgésicos de rescate y fármacos para controlar reacciones adversas, de la misma forma que consultas a profesionales de la salud. Cada paciente manejado con P/L representa un ahorro de COP $1.454.655 al contrario si se manejase con el anticonvulsivante de manera exclusiva, en el caso de G/L este ahorro es de COP $ 25.353.354 frente a G sola.

Distribución hiperbólica generalizada: una aplicación en la selección de portafolios y en la cuantificación de medidas de riesgo de mercado

En este trabajo se implementa una metodología para incluir momentos de orden superior en la selección de portafolios, haciendo uso de la Distribución Hiperbólica Generalizada, para posteriormente hacer un análisis comparativo frente al modelo de Markowitz.

Can the frequency of blocking be described by a red noise process?

The frequency of persistent atmospheric blocking events in the 40-yr ECMWF Re-Analysis (ERA-40) is compared with the blocking frequency produced by a simple first-order Markov model designed to predict the time evolution of a blocking index [defined by the meridional contrast of potential temperature on the 2-PVU surface (1 PVU ≡ 1 × 10−6 K m2 kg−1 s−1)]. With the observed spatial coherence built into the model, it is able to reproduce the main regions of blocking occurrence and the frequencies of sector blocking very well. This underlines the importance of the climatological background flow in determining the locations of high blocking occurrence as being the regions where the mean midlatitude meridional potential vorticity (PV) gradient is weak. However, when only persistent blocking episodes are considered, the model is unable to simulate the observed frequencies. It is proposed that this persistence beyond that given by a red noise model is due to the self-sustaining nature of the blocking phenomenon.

Modelling the partitioning of evapotranspiration in a maize-sunflower intercrop

The primary purpose of this study was to model the partitioning of evapotranspiration in a maize-sunflower intercrop at various canopy covers. The Shuttleworth-Wallace (SW) model was extended for intercropping systems to include both crop transpiration and soil evaporation and allowing interaction between the two. To test the accuracy of the extended SW model, two field experiments of maize-sunflower intercrop were conducted in 1998 and 1999. Plant transpiration and soil evaporation were measured using sap flow gauges and lysimeters, respectively. The mean prediction error (simulated minus measured values) for transpiration was zero (which indicated no overall bias in estimation error), and its accuracy was not affected by the plant growth stages, but simulated transpiration during high measured transpiration rates tended to be slightly underestimated. Overall, the predictions for daily soil evaporation were also accurate. Model estimation errors were probably due to the simplified modelling of soil water content, stomatal resistances and soil heat flux as well as due to the uncertainties in characterising the 2 micrometeorological conditions. The SW’s prediction of transpiration was most sensitive to parameters most directly related to the canopy characteristics such as the partitioning of captured solar radiation, canopy resistance, and bulk boundary layer resistance.

Analysis of the calving pattern of herds in small-scale dairy systems in central Mexico

This study sets out to find the best calving pattern for small-scale dairy systems in Michoacan State, central Mexico. Two models were built. First, a linear programming model was constructed to optimize calving pattern and herd structure according to metabolizable energy availability. Second, a Markov chain model was built to investigate three reproductive scenarios (good, average and poor) in order to suggest factors that maintain the calving pattern given by the linear programming model. Though it was not possible to maintain the optimal linear programming pattern, the Markov chain model suggested adopting different reproduction strategies according to period of the year that the cow is expected to calve. Comparing different scenarios, the Markov model indicated the effect of calving interval on calving pattern and herd structure.

Forecast encompassing tests and probability forecasts

We consider tests of forecast encompassing for probability forecasts, for both quadratic and logarithmic scoring rules. We propose test statistics for the null of forecast encompassing, present the limiting distributions of the test statistics, and investigate the impact of estimating the forecasting models' parameters on these distributions. The small-sample performance is investigated, in terms of small numbers of forecasts and model estimation sample sizes. We show the usefulness of the tests for the evaluation of recession probability forecasts from logit models with different leading indicators as explanatory variables, and for evaluating survey-based probability forecasts.

Visual attention and attribute attendance in multi-attribute choice experiments

Decision strategies in multi-attribute Choice Experiments are investigated using eye-tracking. The visual attention towards, and attendance of, attributes is examined. Stated attendance is found to diverge substantively from visual attendance of attributes. However, stated and visual attendance are shown to be informative, non-overlapping sources of information about respondent utility functions when incorporated into model estimation. Eye-tracking also reveals systematic nonattendance of attributes only by a minority of respondents. Most respondents visually attend most attributes most of the time. We find no compelling evidence that the level of attention is related to respondent certainty, or that higher or lower value attributes receive more or less attention

Dynamic game soundtrack generation in response to a continously varying emotional trajectory

Dynamic soundtracking presents various practical and aesthetic challenges to composers working with games. This paper presents an implementation of a system addressing some of these challenges with an affectively-driven music generation algorithm based on a second order Markov-model. The system can respond in real-time to emotional trajectories derived from 2-dimensions of affect on the circumplex model (arousal and valence), which are mapped to five musical parameters. A transition matrix is employed to vary the generated output in continuous response to the affective state intended by the gameplay.