We present multi-speaker text-to-speech corpora for Javanese and Sundanese, the second and third largest languages of Indonesia spoken by well over a hundred million people. The key objectives were to collect high-quality data in 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 corpora consisting of 5,800 (Javanese) and 4,200 (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 corpus of Standard Indonesian 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 text-to-speech technologies to other lesser resourced languages of Indonesia.
@InProceedings{WIBAWA18.8888, author = {Jaka Aris Eko Wibawa and Supheakmungkol Sarin and Chenfang Li and Knot Pipatsrisawat and Keshan Sodimana and Oddur Kjartansson and Alexander Gutkin and Martin Jansche and Linne Ha}, title = "{Building Open Javanese and Sundanese Corpora for Multilingual Text-to-Speech}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
Summary of the paper