Multilingual Acoustic Models for Speech Recognition in Low-Resource Devices

Multilingual access to information and services is a key requirement in any pervasive or ubiquitous computing environment. In this paper we review the design of a common alphabet for up to fifteen languages and describe its application to multilingual speech recognition in low-resource devices in real-time. We give an overview of the special requirements for acoustic modeling in such environments and present initial results of a technique that aims on a more efficient discrimination between languages in training while keeping low memory footprint. We also report the usefulness of a multilingual recognizer as a language-independent system to bootstrap a new language.