Building acoustic databases for speech recognition is very important for under-resourced languages. To build a speech recognition system, a large amount of speech data from a considerable number of participants needs to be collected. Eyra is a toolkit that can be used to gather acoustic data from a large number of participants in a relatively straight forward fashion. Predetermined prompts are downloaded onto a client, typically run on a smartphone, where the participant reads them aloud so that the recording and its corresponding prompt can be uploaded. This paper presents the Eyra toolkit, its quality control routines and annotation mechanism. The quality control relies on a forced-alignment module, which gives feedback to the participant, and an annotation module which allows data collectors to rate the read prompts after they are uploaded to the system. The paper presents an analysis of the performance of the quality control and describes two data collections for Icelandic and Javanese.
Cite as: Guðnason, J., Pétursson, M., Kjaran, R., Klüpfel, S., Nikulásdóttir, A.B. (2017) Building ASR Corpora Using Eyra. Proc. Interspeech 2017, 2173-2177, doi: 10.21437/Interspeech.2017-1352
@inproceedings{gunason17_interspeech,
author={Jón Guðnason and Matthías Pétursson and Róbert Kjaran and Simon Klüpfel and Anna Björk Nikulásdóttir},
title={{Building ASR Corpora Using Eyra}},
year=2017,
booktitle={Proc. Interspeech 2017},
pages={2173--2177},
doi={10.21437/Interspeech.2017-1352}
}