Crowdsourcing Latin American Spanish for Low-Resource Text-to-Speech

Adriana Guevara-Rukoz, Isin Demirsahin, Fei He, Shan-Hui Cathy Chu, Supheakmungkol Sarin, Knot Pipatsrisawat, Alexander Gutkin, Alena Butryna, Oddur Kjartansson


Abstract
In this paper we present a multidialectal corpus approach for building a text-to-speech voice for a new dialect in a language with existing resources, focusing on various South American dialects of Spanish. We first present public speech datasets for Argentinian, Chilean, Colombian, Peruvian, Puerto Rican and Venezuelan Spanish specifically constructed with text-to-speech applications in mind using crowd-sourcing. We then compare the monodialectal voices built with minimal data to a multidialectal model built by pooling all the resources from all dialects. Our results show that the multidialectal model outperforms the monodialectal baseline models. We also experiment with a “zero-resource” dialect scenario where we build a multidialectal voice for a dialect while holding out target dialect recordings from the training data.
Anthology ID:
2020.lrec-1.801
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
6504–6513
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.801
DOI:
Bibkey:
Cite (ACL):
Adriana Guevara-Rukoz, Isin Demirsahin, Fei He, Shan-Hui Cathy Chu, Supheakmungkol Sarin, Knot Pipatsrisawat, Alexander Gutkin, Alena Butryna, and Oddur Kjartansson. 2020. Crowdsourcing Latin American Spanish for Low-Resource Text-to-Speech. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 6504–6513, Marseille, France. European Language Resources Association.
Cite (Informal):
Crowdsourcing Latin American Spanish for Low-Resource Text-to-Speech (Guevara-Rukoz et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.801.pdf