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48. Al-Fat’h/The Victory

48. Al-Fat’h/The Victory

I/We begin by the Blessed Name of Allah

The Immensely Merciful to all, The Infinitely Compassionate to everyone.

48:01
a. O The Prophet!
b. Indeed, WE have granted you a victory, an outstanding victory.

48:02
a. So that Allah may save you from blames, earlier and subsequent, if any, and
b. complete HIS Favors upon you, and
c. guide you along the Right Path.

48:03
a. Furthermore, Allah may help you with a strong and unparalleled help.

48:04
a. It is HE WHO sent down the spirit of tranquility and assurance onto the hearts of the believers,
b. so they may increase in faith over and above their present level of faith.
c. And to Allah belong the forces of the celestial realm and the terrestrial world,
d. and Allah is All-Knowing of HIS creatures, All-Wise in HIS actions -

48:05
a. so that HE may admit the believing males and believing females into Paradise through which rivers/streams flow to remain therein forever,
b. and that HE may absolve them of their impieties and sinful trespasses.
c. And that will be a great success with Allah.

48:06
a. And HE punishes the hypocrite males and the hypocrite females alike, and
b. the idolatrous males and the idolatrous females -
c. for they think evil notions about Allah.
d. Their evil is going to come back to them by way of abasement and punishment.
e. Allah’s Wrath is upon them, and
f. HE has cursed them,
g. and has prepared Hell for them -
h. and this is going to be a miserable destination!

48:07
a. And to...

Proposing Sociological Research on Children Health Problems in Pakistan

Like many low-income countries, Pakistan is facing children’s health problems. The major health problems affecting children in the country are Pneumonia, Diarrhoea, Measles, Malaria and malnutrition. There is much research has already been conducted on biomedical and epidemiological aspects of these health problems, but little is known about the social and cultural dimensions of children’s health issues. This paper attempts to propose the sociological research on children’s health problems in Pakistan with the emic focus on local context. The proposed future research may mainly be situated in the interpretivist paradigm of qualitative inquiry. Thus, it will contribute in up-scaling the very basic understanding of the meaning formed by people about social determinants of prevailing children health problems and their potential hazardous consequences in Pakistan.

Text-Independent Speaker Verification System for Pashto Speakers With Accent and Dialect Recognition

In this thesis, “a text-independent speaker verification system for Pashto speakers using accent and dialect recognition approach” has been designed. The purpose of the designed system is to recognize the region of origin of Pashto native speakers on the basis of their distinct dialects and to verify them using a speaker verification system. Due to the unavailability of the Pashto voice data in the form of different accents and dialects, a Pashto speakers’ database using different dialects of Pashto was developed. In order to develop the data initially, different dialectical variations of Pashto language were studied in detail and then the speech data was collected only from those different regions of Pakistan and Afghanistan where the Pashto is spoken with different dialects. After the database development, it is processed through front end and feature extraction processes where Mel Frequency Cepstral Coefficient (MFCC) features have been extracted from the collected data. After the MFCC feature vectors have been obtained, a Multilayer Perceptron (MLP) based classifier was designed to classify the speakers. Two separate classification experiments were performed (1) Speaker identification followed by dialect identification (2) Text-independent speaker verification followed by dialect identification. Speaker identification followed by dialect identification achieved 96.0 % identification accuracy, whereas, speaker verification followed by dialect identification achieved 100 % verification accuracy. Furthermore, the proposed Gaussian Mixture Model (GMM) based dialect identification system achieved 93.8 % identification accuracy in identifying Pashto native dialects. In order to inspect the noise robustness of the proposed system, the system’s performance was checked with the different degrees of noise level and Signal to Noise Ratio (SNR) was computed for each degree of noise. The performance of the system showed slightly degradation with the increase in the noise level, hence, showed its robustness against noise. A simple Pashto digits recognition (1 to 10 digits of Pashto) was also included in the study using MLP, HMM & SVM classifiers. Comparative analysis showed that the SVM based Pashto digit recognizer with 98.5 % recognition accuracy outperformed both the MLP and HMM based Pashto digit recognizers by showing 1.3 % and 3.3 % improvement in recognition accuracy. In order to benchmark the proposed research, the system’s performance was further tested on classifying some foreign accent of Pashto (Urdu accent of Pashto). In case of classifying the Urdu accent of Pashto, the system achieved 74.4 % recognition accuracy. Finally, the results achieved in the conducted experiments were compared with the recently proposed state of the art dialect identification, speaker verification and Pashto digit recognition systems. Comparative study showed that the proposed system outperformed some recently proposed dialect identification as well as speaker verification systems and showed relative improvement in recognition accuracies.
Asian Research Index Whatsapp Chanel
Asian Research Index Whatsapp Chanel

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