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Most of current end-to-end speech synthesis assumes the input text is in a single language situation. However, codeswitching in speech occurs frequently in routine life, in which speakers switch between languages in the same utterance. And building a large mixed-language speech database is difficult and uneconomical. In this paper, both windowing technique and style token modeling are designed for the code-switching endto-end speech synthesis. To improve the consistency of speaking style indoi:10.21437/interspeech.2020-1754 dblp:conf/interspeech/FuTWYQW20 fatcat:axfpfvlqe5e6fmfmscxzaso274