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Multiple accents are often present in spontaneous Chinese Mandarin speech as most Chinese have learned Mandarin as a second language. We propose a method to handle multiple accents as well as standard speech in a speaker-independent system by merging auxiliary accent decision trees with standard trees and reconstruct the acoustic model. In our proposed method, tree structures and shape are modified according to accent-specific data while the parameter set of the baseline model remains the same. The effectiveness of this approach is evaluated on Cantonese and Wu accented, as well as standard Mandarin speech. Our method yields a significant 4.4% and 3.3% absolute word error rate reduction without sacrificing the performance on standard Mandarin speech.