AI

Building Open Javanese and Sundanese Corpora for Multilingual Text-to-Speech

Abstract

We present the multi-speaker text-to-speech corpora for Javanese and Sundanese languages, the second and third biggest languages of Indonesia spoken by well over a hundred million people. The key objectives were to collect the high-quality data an affordable way and to share the data publicly with the speech community. To achieve this, we collaborated with two local universities in Java and streamlined our recording and crowdsourcing processes to produce the corpora consisting of 5.8 thousand (Javanese) and 4.2 thousand (Sundanese) mixed-gender recordings. We used these corpora to build several configurations of multi-speaker neural network-based text-to-speech systems for Javanese and Sundanese. Subjective evaluations performed on these configurations demonstrate that multilingual configurations for which Javanese and Sundanese are trained jointly with a larger Indonesian corpus significantly outperform the systems constructed from a single language. We hope that sharing these corpora publicly and presenting our multilingual approach to text-to-speech will help the community to scale up the text-to-speech technologies to other lesser resourced languages of Indonesia.