A novel approach is proposed to creating a polyglot speech synthesis system without the need of collecting speech data from a bilingual (or multilingual) speaker, which is often expensive or even infeasible. Given a target speaker with data in the first language (Mandarin in this study), the basic idea is to construct artificial utterances in the second language (English) via selection of speech sample frames of the given speaker in the first language. As the speaker needs not be polyglot, this method is generally applicable to any speaker and any languages. In the search for optimal frame sequence selection, the candidate set is constrained by a decision tree for phone segments in the speech data of both languages, and the cost function depends on the context-dependent articulatory and auditory features. Evaluation results show that good performance regarding similarity (speaker identity) and naturalness (speech quality) can be achieved with the proposed method.