  This study investigates whether phonological features can be applied in
text-to-speech systems to generate native and non-native speech in English and
Mandarin. We present a mapping of ARPABET/pinyin to SAMPA/SAMPA-SC and then to
phonological features. We tested whether this mapping could lead to the
successful generation of native, non-native, and code-switched speech in the
two languages. We ran two experiments, one with a small dataset and one with a
larger dataset. The results proved that phonological features could be used as
a feasible input system, although further investigation is needed to improve
model performance. The accented output generated by the TTS models also helps
with understanding human second language acquisition processes.
