[2305.07445] QVoice: Arabic Speech Pronunciation Learning Application
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Electrical Engineering and Systems Science > Audio and Speech Processing

arXiv:2305.07445 (eess)
[Submitted on 9 May 2023]

Title:QVoice: Arabic Speech Pronunciation Learning Application

Authors:Yassine El Kheir, Fouad Khnaisser, Shammur Absar Chowdhury, Hamdy Mubarak, Shazia Afzal, Ahmed Ali
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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.
Comments: 2 pages, Accepted InterSpeech23 Show & Tell Demo Session
Subjects: Audio and Speech Processing (eess.AS); Computation and Language (cs.CL); Sound (cs.SD)
Cite as: arXiv:2305.07445 [eess.AS]
  (or arXiv:2305.07445v1 [eess.AS] for this version)
  https://doi.org/10.48550/arXiv.2305.07445
Journal reference: InterSpeech 2023

Submission history

From: Yassine Elkheir [view email]
[v1] Tue, 9 May 2023 07:21:46 UTC (2,943 KB)
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