Automatic Pronunciation Assessment

Automatic pronunciation assessment (APA) aims to objectively evaluate the pronunciation proficiency of non-native speakers, typically focusing on aspects like accuracy, fluency, and prosody at various granularities (phoneme, word, sentence). Recent research emphasizes improving APA models by incorporating contrastive learning, hierarchical modeling, and multi-task learning frameworks, often leveraging transformer networks and pre-trained acoustic models like HuBERT. These advancements aim to address challenges such as data scarcity, imbalanced datasets, and the need for more phoneme-aware and context-sensitive assessments, ultimately leading to more effective computer-assisted pronunciation training tools.