We propose to improve speech recognition performance on speaker-independent, mixed language speech by asymmetric acoustic modeling. Mixed language is either inter-sentential code switching from the source matrix language to a foreign language or intra-sentential code mixing between the matrix language and embedded foreign words or phrases. In either case, the foreign phrases are pronounced by the matrix language speaker with varying degrees of accent. Our proposed system using selective decision tree merging between a bilingual model and an accented embedded speech model outperforms previous approaches of either using a bilingual