Applying Phonological Features in Multilingual Text-To-Speech

This study investigates whether phonological features can be applied in text-to-speech systems to generate native and non-native speech. We present a mapping between ARPABET/pinyin->SAMPA/SAMPA-SC->phonological features in this paper, and tested whether native, non-native, and code-switched speech could be successfully generated using this mapping. We ran two experiments, one with a small dataset and one with a larger dataset. The results proved that phonological features can be a feasible input system, although it needs further investigation to improve model performance. The accented output generated by the TTS models also helps with understanding human second language acquisition processes.