rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Modeling for recognizing recitation type of the Holy Qur'an
  name:
    name part: Yousfi, Bilal
    role:
      role term: creator
    role:
      role term: author
  name:
    name part: Akram M Z M Khedher
    role:
      role term: degree supervisor
  name:
    name part: International Islamic University Malaysia
    name part: Kulliyyah of Information and Communication Technology
  type of resource: text
  genre: theses
  genre: Theses, IIUM local
  origin info:
    place:
      place term: my
    date issued: 2021
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: xi, 157 leaves : illustrations ; 30 cm.
  abstract: Computer science and speech recognition have enjoyed a long and fruitful relationship for decades. Speech recognition has been beneficial for capturing and producing an accurate transcription of spoken words. In computer science, a prime challenge is to interpret these signals into meaningful data and to develop algorithms and applications to establish an interface between the human’s voice signal and computer. Moreover, the major concerns of automatic speech recognition (ASR) are determining a set of classification features and finding a suitable recognition model for these features. Hidden Markov Models (HMMs) have been demonstrated to be powerful models for representing time-varying signals. The act of reading Qur’ān and pronouncing its sound dwells on the type of recitation. These are referring to the recitation of Warsh or the recitation of Hafss. According to the science of Qira’āt, it is essential to recognize the type of recitations, especially with the diversity and the spread of Qira’āt in the world. There are numerous efforts made by previous systems on the development of feasible guiding techniques to the act of reading the Holy Qur’ān (Tajweed rules). Unfortunately, liking the major control variables of the practices of both Usūl al Qira’āh (general principles) and Farsh al-huruf (specific variants) in those approaches were neglected. In order to fill this gap, this research thesis attempts to design and fabricate a speech recognition system that distinguishes the types of recitations (Qira’āt of Hafss An Assim and the Qira’āt of Warsh An Naafi’) while reciting the Qur’ān. The proposed system is capable of recognizing, identifying, pointing out the mismatch and discriminate between two types recitations for Hafss and Warsh. An experiment among user’s recitation for Hafss and Warsh with the recitation made by the expert Qur’ān reader stored in a database has been done. This thesis investigates acoustic models based on the Hidden Markov Models (HMM) class…
  target audience: specialized
  note: by Bilal Yousfi
  note: Abstracts in English and Arabic.
  note: "A thesis submitted in fulfilment of the requirement for the degree of Doctor of Philosophy in Computer Science." --On title page.
  note: Thesis (Ph.D)--International Islamic University Malaysia, 2021.
  note: Includes bibliographical references (leaves 152-156).
  subject:
    geographic code: a-my---
  subject:
    topic: Automatic speech recognition
  subject:
    title info:
      title: Qur’an
    topic: Qira’at
    topic: Dialects
  subject:
    title info:
      title: Qur’an
    topic: Tilawah
  classification: TK7895.S65
  identifier: http://studentrepo.iium.edu.my/handle/123456789/11168
  record info:
    record content source: UIAM
    record creation date: 230127
    record change date: 20230301160924.0
    language of cataloging:
      language term: eng