Language identification oriented to Multilingual Speech Recognition in the Basque context

Abstract

Automatic Speech Recognition (ASR) is a broad research area that absorbs many efforts from the research community. Robust speech recognition systems can be applied to automation of houses, office or business, monitoring of manufacturing processes, automation of telephone or telecommunication services. The development of Multilingual Large Vocabulary Continuous Speech Recognition systems involves issues as: Language Identification, Acoustic Phonetic Decoding, Language Modelling or the development of appropriated Language Resources. The interest on Multilingual Systems arouses because there are three official languages in the Basque Country (Basque, Spanish, and French), and there is much linguistic interaction among them, even if Basque has very different roots than the other two languages. This paper describes the development of a Language Identification (LID) system oriented to robust Multilingual Speech Recognition for the Basque context. The work presents hybrid strategies for LID, based on the selection of system elements by Support Vector Machines and Multilayer Perceptron classifiers and stochastic methods for speech recognition tasks (Hidden Markov Models and n-grams).