Markov Model Based Oriya Isolated Speech Recognizer-An Emerging Solution for Visually Impaired Students in School and Public Examination

In this paper we have tried to focus on problems faced by visually impaired students of Orissa in school and public examinations and discussed the emerging solutions to those problems at the end in order to minimize those problems. Assessment plays an important role in the education system for evaluating student’s skill in that area. Assessment can be carried out by allowing students to appear exam in terms objective or non-objective type questions but due to the advantages offered by objective type assessment like offer speedier marking, reduced need for cross marking, greater fairness (reliability), more coverage of the syllabus and finally automate the marking process which enforces examination system to be held as objective rather non-objective type. Therefore, it is mostly implemented in examination system conducted in public or school exams. But it is very regret to mention that this assessment procedure is not well suitable for students those are visually impaired as they are unable to read what they have written or it is not possible to know if the ribbon has run out or if the line spacing is faulty unless the supervisor tells them. These are the main obstacles faced by visually challenged people which lead to disqualification for higher studies that ultimately reason to failure of motto i.e. “Education for All”. In this research study we have considered close ended objective type question. All possible responses of the closed questions are designed such a way that they are mutually exclusive. The closed ended questions are of five types namely fill-in-the-blanks questions, dichotomous questions, ranking scale questions, multiple choice questions and rating scale questions. As all the answers to the above types of questions carry isolated answers, we have developed Oriya isolated speech recognition system which can easily convert isolated answers uttered by visually impaired students to isolated text(isolated speech to isolated text). Hence, visually impaired students can answer the question as normal student because they do not need at all their hand and eyes to respond the answer. As a result of which overcomes the problem faced by visually challenged people to answer the questions without help of keyboard. Oriya isolated recognition system is developed using hidden Markov Model by incorporating1800 isolated Oriya words collected from 30 speakers in training stage. Testing stage is carried out by considering 5 speakers which yields 76.23% word accuracy on seen data and 58.86% on unseen data

Emotion Recognition using Fuzzy K-Means from Oriya Speech

Communication will be intelligible when conveyed message is interpreted in right-minded. Unfortunately, the rightminded interpretation of communicated message is possible for human-human communication but it’s laborious for humanmachine communication. It is due to the inherently blending of non-verbal contents such as emotion in vocal communication which leads to difficulty in human-machine interaction. In this research paper we have performed experiment to recognize emotions like anger, sadness, astonish, fear, happiness and neutral using fuzzy K-Means algorithm from Oriya elicited speech collected from 35 Oriya speaking people aged between 22- 58 years belonging to different provinces of Orissa. We have achieved the accuracy of 65.16% in recognizing above six mentioned emotions by incorporating mean pitch, first two formants, jitter, shimmer and energy as feature vectors for this research work. Emotion recognition has many vivid applications in different domains like call centers, spoken tutoring systems, spoken dialogue research, human-robotic interfaces etc

Indian Language Compatible Intelligent User Interfaces

Implicit Human Computer Interaction to explicit context-dependent knowledge processing to meet the requirements of intelligent human being in the present day situation has provoked scientist towards the development of Intelligent User Interfaces to face the society with a demand of smart devices, embedded to the smart environment and dynamic activities. Context-aware situation deals with location and situation focused context like virtual car navigation to context with respect to traffic to climate to the human connected with it immediately and afterwards

POPULATION STRUCTURE OF KAEMPFERIA GALANGA L. FROM EASTERN INDIA

Objective: India has been a producer of a large number of aromatic medicinal plants which serves as a valuable genetic resource for future quality improvement to meet the ever-growing demand of human essential products. Thus, an urgent need arises for germplasm conservation of these high yielding varieties to help the pharmaceutical and other industries. For this understanding, the population structure is essential in order to explore their genetic identification by fingerprinting and molecular characterization. Methods: In the present study DNA was isolated using modified Cetyl Trimethyl Ammonium Bromide (CTAB) method and Polymerase Chain Reaction (PCR) was performed according to standardized method along with its data analysis. This study was undertaken to characterize the highly medicinal Kaempferia galanga collected from 4 different populations of Odisha using the molecular markers as Random Amplified Polymorphic DNA and Inter-Simple Sequence Repeats for the first time. Results: A dendrogram constructed through Sequential Agglomerative Hierarchical and Nested (SAHN) clustering and Unweighted Pair Group Method with Arithmetic mean (UPGMA) analysis showed an average similarity of 0.993 ranging between 0.967 to 1.000. Jaccard’s similarity coefficient of combined markers segregated the genotypes into two main clusters, 1 with six samples and the others at 0.98 similarity coefficient. Conclusion: Hence, the molecular analysis could be further used for the identification of important novel gene present in Kaempferia galanga which can be utilized for future crop improvement as well as pharmacological activities

Assessment of genetic diversity of Curcuma aromatica from eastern India using ISSR and RAPD markers

Application of Inter Simple Sequence Repeats and Random Amplified Polymorphic DNA markers in Curcuma aromatica collected from 4 different populations of Odisha. A dendrogram was constructed through sequential agglomerative hierarchial and nested (SAHN) clustering and unweighted pair group method with arithmetic mean (UPGMA) analysis using Jaccard’s similarity coefficient of combined markers using this particular species. Two major clusters were found i.e., cluster-I (Koraput-1, Koraput-2, Koraput-3, G.Udaigiri-1, G.Udaigiri-2, G.Udaigiri-3 and Phulabani-1, Phulabani-2, Phulabani-3) and cluster-II (Raikia-1, Raikia-2 and Raikia-3). The clustering pattern also revealed moreover the extent of genetic similarity between germplasms collected from those populations. This technique would be further utilized for identification and tagging of important novel gene present in different taxa or improvement work in family Zingiberaceae. This study would be of immense significance for conservation and characterization of important medicinal plant species

An Approach to Extract Feature Using MFCC for Isolated Word in Speaker Identification System

The speech is the prominent and natural form of communication among human being. There are different aspects related to speech like speaker identification, speaker recognition, Automatic speech recognition(ASR), speech synthesis etc. The purpose of this work is to study speaker identification system using Hidden markov Model (HMM).The goal of Speaker Identification System (SIS) is to determine which speaker is speaking based on spoken information. The system uses Mel Frequency Cepstral Coefficients(MFCC) for feature extraction , HMM for pattern training and viterbi techniques. The success of MFCC combined with their robust and cost effective combination turned them into a standard choice in speaker identification system.HMM and viterbi decoding provide a highly reliable way of recognizing odia speech

Comparative evaluation of non enzymatic antioxidants, vitamin C and albumin in patients suffering from different grades of periodontitis: a retrospective observational study

Background: Rate of degree of destruction of periodontium may be associated with the oxidative stress due to the imbalance of different serum antioxidants. The objective of this study is to compare the evaluated concentrations of non enzymatic antioxidants like vit-C, albumin levels and total antioxidant status, from the available data of patients with slowly and rapidly progressive periodontitis (RPP). Methods: This retrospective observational study was confined to a study population, which include; 42 patients with RPP, 42 patients with slowly progressive periodontitis (SPP) and 86 healthy controls, in whom the required data were available. The levels of non enzymatic antioxidants like albumin, vitamin C and total antioxidant capacity (TAC) of patients, suffering from RPP, are compared with SPP and healthy controls. Results: The values of serum albumin and vitamin-c levels in RPP even remaining within the normal ranges were found to be on the lower side, when compared with healthy controls. The systemic TAC levels were found to be at a lower side in both SPP and RPP, when compared with the healthy control group.   Conclusions: The systemic levels of non enzymatic antioxidants, vit C and albumin, in RPP were found to be on the lower side, even remaining within the normal ranges, when compared with the healthy controls. The TAC in SPP and RPP is also found to be on lower side, consistent with previous studies.

Impact of Catheter Ablation on Quality of Life and Healthcare Utilisation

Impairment of quality of life (QoL) is a well-known complication of AF. Because of the association of AF with older age and many other cardiovascular comorbidities, there are multiple factors that could influence QoL score even after successful AF intervention. However, substantial improvement in QoL has been reported following catheter ablation for AF regardless of ablation outcomes. In terms of healthcare resource utilisation, the expenses associated with AF are very high because of the hospitalisations for AF-related thromboembolic complications, aggravation of heart failure, AF interventions, and emergency room visits for incessant arrhythmia episodes, and they represent a large economic burden worldwide. Several trials have shown a drastic reduction in healthcare costs following successful AF ablation. In this review, the authors discuss this evidence systematically