QVoice: Arabic Speech Pronunciation Learning Application

Yassine El Kheir, Fouad Khnaisser, Shammur Absar Chowdhury, Hamdy Mubarak, Shazia Afzal, Ahmed Ali

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper introduces a novel Arabic pronunciation learning application QVoice, powered with end-to-end mispronunciation detection and feedback generator module. The application is designed to support non-native Arabic speakers in enhancing their pronunciation skills, while also helping native speakers mitigate any potential influence from regional dialects on their Modern Standard Arabic (MSA) pronunciation. QVoice employs various learning cues to aid learners in comprehending meaning, drawing connections with their existing knowledge of English language, and offers detailed feedback for pronunciation correction, along with contextual examples showcasing word usage. The learning cues featured in QVoice encompass a wide range of meaningful information, such as visualizations of phrases/words and their translations, as well as phonetic transcriptions and transliterations. QVoice provides pronunciation feedback at the character level and assesses performance at the word level.

Original languageEnglish
Pages (from-to)3677-3678
Number of pages2
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume2023-August
Publication statusPublished - 2023
Event24th International Speech Communication Association, Interspeech 2023 - Dublin, Ireland
Duration: 20 Aug 202324 Aug 2023

Keywords

  • Arabic pronunciation learning
  • Mispronunciation detection model
  • automatic scoring

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