The complementary roles of non-verbal cues for Robust Pronunciation Assessment

Kheir, Yassine El, Chowdhury, Shammur Absar, Ali, Ahmed

arXiv.org Artificial Intelligence 

Numerous investigations have explored a range of features and modeling approaches aimed at enhancing modeling Research on pronunciation assessment systems focuses performance. These explorations have encompassed the utilization on utilizing phonetic and phonological aspects of non-native of Goodness-of-Pronunciation (GOP) metrics [4, 5, (L2) speech, often neglecting the rich layer of information 6], the integration of manually crafted handful of non-verbal hidden within the non-verbal cues. In this study, we proposed features such as duration, energy, and pitch [7, 8, 9], as well a novel pronunciation assessment framework, IntraVerbalPA.

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