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End-to-end text-to-speech (TTS) systems has proved its great successin the presence of a large amount of high-quality training data recorded inanechoic room with high-quality microphone. Another approach is to useavailable source of found data like radio broadcast news. We aim to optimizethe naturalness of TTS system on the found data using a novel data processingmethod. The data processing method includes 1) utterance selection and 2)prosodic punctuation insertion to prepare training data which can optimize thenaturalness of TTS systems. We showed that using the processing data method, anend-to-end TTS achieved a mean opinion score (MOS) of 4.1 compared to 4.3 ofnatural speech. We showed that the punctuation insertion contributed the mostto the result. To facilitate the research and development of TTS systems, wedistributed the processed data of one speaker athttps://forms.gle/6Hk5YkqgDxAaC2BU6.

Data Processing for Optimizing Naturalness of Vietnamese Text-to-speech System