Spoken English Assessment Using Confused Phoneme Assessment Model - Zhaoxia Jiang (Mobile Information Systems, 2021)
Under normal circumstances, in the process of evaluating the phoneme of spoken English which is easy to be confused, it is impossible to accurately assess the oral ability of different groups of people according to their oral ability. The assessment process has problems of poor robustness and low stability. We propose a spoken English assessment method based on an easily confused phoneme assessment model to address these problems. We design an English easily confused phoneme-based evaluation model in the proposed framework by adopting fuzzy logic for the assessment task. We also present HPD set for confused phonemes and introduce the easily confused phonemes in spoken English. Moreover, we derive four fuzzy measure assessment grades of E/G/NI/GR and present the assessment model for them. We continuously recognize and annotate spoken English to find the best-matched statement and complete the recognition and assessment of easily confused phoneme. Then, we also focus on spoken English assessment based on an easily confused phoneme assessment model. Empirical results demonstrate the superior performance of our proposed models over the conventional evaluation methods. Our proposed models improve the spoken English assessment method by 30% and the stability by 45%. Besides, our model is also suitable for the spoken English assessment of different groups of people.