1. Introduction 2. How to Use this Encyclopedia 3. Editorial Board 4. List of Contributors 5. Alphabetical List of Entries 6. Entries A to Z 7. Bibliographical Rescources 8. Qur'anic Passages Index 9. Name Index 10. Subject Index

The Qurʾan : an encyclopedia

https://cyberleninka.org/article/n/103718.pdf

Building CMU Sphinx language model for the Holy Quran using simplified Arabic phonemes

Speech-based intelligent systems using deep learning are becoming increasingly important due to their wide range of applications in our routine life. Most of the efforts on voice signal processing are limited for the English language. However, little effort has focused on voice signal processing for the Arabic language or for the Quran, which is the central religious book of Islam. In this study, our objective is to develop a deep learning based speaker identification using Quran recitations. We propose the use of Bidirectional Long Short-Term Memory (BLSTM)– a type of Recurrent Neural Networks (RNNs), which are well known for being particularly suitable for speech modeling and processing–for the task of Quranic speaker identification. Our results show that our BLSTM-based Quranic speaker identification delivers significantly improved results compared to previous approaches and is also computationally less expensive.

Quran Reciter Identification: A Deep Learning Approach

Performance Measurement Of Mel Frequency Ceptral Coefficient (MFCC) Method In Learning System Of Al- Qur’an Based In Nagham Pattern Recognition

Voice signal processing has been proposed to improve effectiveness and facilitate the public, such as Smart Home. This study aims a smart home simulation model to move doors, TVs, and lights from voice instructions. Sound signals are processed using Mel-frequency Cepstrum Coefficients (MFCC) to perform feature extraction. Then, the voice is recognized by the speaker using a hierarchy Support Vector Machine (SVM). So that unregistered speakers are not processed or are declared not having access rights. For the process of recognizing spoken words such as “Open the Door”,“Close the Door”,“Turn on the TV”,“Turn off the TV”,“Turn on the Lights” and “Turn Off the Lights” are done using Backpropagation. The results showed that hierarchy SVM provided an accuracy of 71% compared to the single SVM of 45%.

https://journal.portalgaruda.org/index.php/EECSI/article/download/1969/1413

Speaker and Speech Recognition Using Hierarchy Support Vector Machine and Backpropagation

This article presents a new application of recitation verification based on correct makhraj. Traditionally, people learn how to recite al-Quran correctly from an expert where it takes lots of time and effort. In this work, a new way to learn reciting the al-Quran is proposed in order to reduce the duration of learning from the expert. A system using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and Mean Square Error (MSE) as a pattern matching technique is considered in order to develop a makhraj recognition system. An experiment has been setup to measure the system performance in terms of accuracy based on False Reject Rate (FRR) and Wrong Recognition (WR).

http://www.aicit.org/IJIIP/ppl/IJIIP129PPL.pdf

Makhraj Recognition for Al-Quran Recitation using MFCC

We demonstrate the optical performance of passively mode-locked pulses in erbium-doped fiber laser incorporating gold-nanoparticles (Au-NPs) as a saturable absorber (SA). Au-NPs of diameters between 5 to 15 nm were synthesized using the pulsed laser ablation method and blended with polydimethylsiloxane polymer. The resulting nanocomposite was deposited on the tapered region of a microfiber with a spin-coating method. The proposed Au-NPs SA recorded a modulation depth of 0.4% and low saturation intensity of 0.1 MW/cm2 leading to stable mode-locking operation in the erbium-doped fiber laser cavity at a low threshold pump power of about 45.6 mW. A mode-locked pulse train with a duration of 933 fs, pulse repetition rate of 6.25 MHz, and peak-to-pedestal extinction ratio of 54.1 dB was achieved at a pump power of 168.1 mW. The obtained results demonstrate that the spherical Au-NPs synthesized by pulsed laser ablation is a feasible material for SA fabrication, validating its saturable absorption properties in a 1.55 μm wavelength region. 

Pulsed-laser-ablated gold-nanoparticles saturable absorber for mode-locked erbium-doped fiber lasers

Effect of Gold-Nanoparticle Size on Microfiber Saturable Absorber for Mode-locked Erbium-doped Fiber Lasers

We demonstrate the generation of 743 fs soliton pulses in erbium-doped fiber laser employing gold-nanoparticles saturable absorber. The mode-locking operation is achieved with gold-nanoparticles/polydimethyl-siloxane composite coated on a microfiber with $\displaystyle \mathbf{10\ \mu m}$. waist diameter, indicating the availability of fabricated saturable absorber for pulsed operation in $\displaystyle \mathbf{1.55\ \mu m}$ spectral range.

Noor Zirwatul Ahlam Naharuddin

Papers

Makhraj Recognition for Al-Quran Recitation using MFCC

Pulsed-laser-ablated gold-nanoparticles saturable absorber for mode-locked erbium-doped fiber lasers

Effect of Gold-Nanoparticle Size on Microfiber Saturable Absorber for Mode-locked Erbium-doped Fiber Lasers

Gold-Nanoparticles Microfiber Saturable Absorber for Mode-Locked Erbium-doped Fiber Laser