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Pronunciation Scoring in Computer-Assisted Language Learning

Mohammadi, Sajede | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55580 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Sameti, Hossein
  7. Abstract:
  8. Due to the increase in the number of people interested in learning new languages, in recent years, multiple systems have been developed to teach new languages to those who are interested. These systems are called Computer Assisted Language Learning (CALL). However, the most credible CALL systems, like Duolingo, do not support Persian. So the of this study is to design and implement one of the technical parts of CALL systems, the Computer Assisted Pronunciation Training(CAPT), which is the part responsible for evaluating the learners' input voice's pronunciation and generating appropriate score and feedback.In this study, good pronunciation means correct expression of words, correct expression of phonemes, and similarity between learners' and reference speaker's speech tone. The corresponding sections for each of these have been used or implemented for the Persian language. Verification of word expression is the responsibility of the Automatic Speech Recognition(ASR) system based on the Vosk-API, which can be replaced with Nevisa, for better accuracy. Also, to check the correct expression of phonemes, due to the lack of a Persian Phoneme Recognition(PR) system with appropriate accuracy, the wav2vec2, which is a popular framework for speech recognition and phoneme recognition tasks, was fine-tuned. And for investigating the similarity of speech tone, classical algorithms of signal processing, normalization, and Cross-Correlation have been used
  9. Keywords:
  10. Computer Assisted Language Learning (CALL) ; Signal Processing ; Automatic Speech Recognition ; Phoneme Recognition ; Wav2vec2 Model ; Computer Assisted Pronunciation Training ; Persian Pronounciation Scoring

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