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This paper presents a large-scale analysis of L2 Korean pronunciation errorpatterns from five different language backgrounds, Chinese, Vietnamese,Japanese, Thai, and English, by using automatic phonetic transcription. For theanalysis, confusion matrices are generated for each L1, by aligning canonicalphone sequences and automatically transcribed phone sequences obtained fromfine-tuned Wav2Vec2 XLS-R phone recognizer. Each value in the confusionmatrices is compared to capture frequent common error patterns and to specifypatterns unique to a certain language background. Using the Foreign Speakers'Voice Data of Korean for Artificial Intelligence Learning dataset, common errorpattern types are found to be (1) substitutions of aspirated or tenseconsonants with plain consonants, (2) deletions of syllable-final consonants,and (3) substitutions of diphthongs with monophthongs. On the other hand,thirty-nine patterns including (1) syllable-final /l/ substitutions with /n/for Vietnamese and (2) /\textturnm/ insertions for Japanese are discovered aslanguage-dependent.

Comparison of L2 Korean pronunciation error patterns from five L1 backgrounds by using automatic phonetic transcription