A Study on Bilingual Speech Recognition Involving a Minority Language

Multilingual Automatic Speech Recognition (ASR) systems are of great interest in multilingual environments. We have studied the case of the Comunitat Valenciana because the two official languages are Spanish and Valencian. These two languages share most of their phonemes and their syntax and vocabulary are also quite similar since they have influenced each other for many years. In this work, we present the design of the language and the acoustic models for this bilingual situation. Acoustic models can be separate for each language or shared by both of them, and they can be obtained directly from a training corpus or by adapting a previous set of acoustic models. Language models can be separate for each language (monolingual recognition) or mixed for both languages (bilingual recognition). We performed experiments with a small corpus to determine which option was better for this case.

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