Prosodic features for automatic text-independent evaluation of degree of nativeness for language learners
نویسندگان
چکیده
Predicting the degree of nativeness of a student's utterance is an important issue in computer-aided language learning. This task has been addressed by many studies focusing on the segmental assessment of the speech signal. To achieve improved correlations between human and automatic nativeness scores, other aspects of speech should also be considered, such as prosody. The goal of this study is to evaluate the use of prosodic information to help predict the degree of nativeness of pronunciation, independent of the text. A supervised strategy based on human grades is used in an attempt to select promising features for this task. Preliminary results show improvements in the correlation between human and automatic scores.
منابع مشابه
Evaluation of Speaker’s Degree of Nativeness Using Text-independent Prosodic Features
Giving feedback on the degree of nativeness of a student’s speech is an important aspect of computer-aided language learning. This task has been addressed by many studies focusing on the segmental assessment of the speech signal. To better model human nativeness scores, other aspects of speech should also be considered, such as prosody. This study examines the use of prosodic information to eva...
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