# Applying Phonological Features in Multilingual Text-To-Speech

arXiv: https://arxiv.org/abs/2110.03609 · HTML: https://mlsanity.com/paper/2110.03609/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 24 references that are in the map.
- First posted on arXiv 7 Oct 2021.

## Builds on (most cited first, 3 of 3)

- [MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis](https://mlsanity.com/paper/1910.06711/) (2019)
- [Phonological Features for 0-shot Multilingual Speech Synthesis](https://mlsanity.com/paper/2008.04107/) (2020)
- [Building a mixed-lingual neural TTS system with only monolingual data](https://mlsanity.com/paper/1904.06063/) (2019)

## Abstract (arXiv)

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.