English in South Asia and Pedagogical Implications

English at present maintains a significant role as a second or foreign language in the region of South Asia as well as globally. In a discussion of this topic, it is important to explore a brief history of the expansion of English and its origins in South Asia. It is also essential to provide a background of South Asian English and its unique linguistic characteristics as well as its use in different contexts of South Asia. The perspectives of linguists and educators who are native to the region of South Asia should be included as much as possible in this research. The most crucial element in this discussion is the various implications of the role of English in South Asia on English language pedagogical practices. The numerous options for how to teach the language and the diverse contexts in which the language may be used have a profound effect on the English language educational approach. These implications lead to examining and suggesting the seemingly most relevant and effective approaches to English language instruction in South Asia. The main question in response to these considerations is what variety of English or instructional model should be taught or used in a South Asian classroom. Based on the diverse cultural context of South Asia and the global state of our world, this research endorses a polymodel of English pedagogy that incorporates the use of an established variety of English primarily for instruction while also exposing students to many more existing varieties that they may encounter as well as the cultures that use them

CMFRI Newsletter No.099 July- September 2003

Abstract not availabl

Improving the role of language model in statistical machine translation (Indonesian-Javanese)

The statistical machine translation (SMT) is widely used by researchers and practitioners in recent years. SMT works with quality that is determined by several important factors, two of which are language and translation model. Research on improving the translation model has been done quite a lot, but the problem of optimizing the language model for use on machine translators has not received much attention. On translator machines, language models usually use trigram models as standard. In this paper, we conducted experiments with four strategies to analyze the role of the language model used in the Indonesian-Javanese translation machine and show improvement compared to the baseline system with the standard language model. The results of this research indicate that the use of 3-gram language models is highly recommended in SMT

An optimization framework for solving capacitated multi-level lot-sizing problems with backlogging

This paper proposes two new mixed integer programming models for capacitated multi-level lot-sizing problems with backlogging, whose linear programming relaxations provide good lower bounds on the optimal solution value. We show that both of these strong formulations yield the same lower bounds. In addition to these theoretical results, we propose a new, effective optimization framework that achieves high quality solutions in reasonable computational time. Computational results show that the proposed optimization framework is superior to other well-known approaches on several important performance dimensions

Arabic digits speech recognition and speaker identification in noisy environment using a hybrid model of VQ and GMM

This paper presents an automatic speaker identification and speech recognition for Arabic digits in noisy environment. In this work, the proposed system is able to identify the speaker after saving his voice in the database and adding noise. The mel frequency cepstral coefficients (MFCC) is the best approach used in building a program in the Matlab platform; also, the quantization is used for generating the codebooks. The Gaussian mixture modelling (GMM) algorithms are used to generate template, feature-matching purpose. In this paper, we have proposed a system based on MFCC-GMM and MFCC-VQ Approaches on the one hand and by using the Hybrid Approach MFCC-VQ-GMM on the other hand for speaker modeling. The White Gaussian noise is added to the clean speech at several signal-to-noise ratio (SNR) levels to test the system in a noisy environment. The proposed system gives good results in recognition rate