Building an Open Source Automatic Speech Recognition System for Catalan

Catalan is recognized as the largest stateless language in Europe hence it is a language well studied in the field of speech, and there exists various solutions for Automatic Speech Recognition (ASR) with large vocabulary. However, unlike many of the official languages of Europe, it neither has an open acoustic corpus sufficiently large for training ASR models, nor openly accessible acoustic models for local task execution and personal use. In order to provide the necessary tools and expertise for the resource limited languages, in this work we discuss the development of a large speech corpus of broadcast media and building of an Catalan ASR system using CMU Sphinx. The resulting models have a WER of 35,2% on a 4 hour test set of similar recordings and a 31.95% on an external 4 hour multi-speaker test set. This rate is further decreased to 11.68% with a task specific language model. 240 hours of broadcast speech data and the resulting models are distributed openly for use.