Arabic and English speech recognition using cross-language acoustic models

In recent years there has been an increasing interest in speech and language processing systems dedicated to Arabic language. In order to perform adequate design and evaluation of those systems, speech databases are needed. The aim of this paper is to evaluate the design of Arabic and English speech recognition systems by using common acoustic models. Cross-language experiments between Arabic and English are conducted and discussed with respect to the main class of phonemes in each language. The LDC WestPoint Arabic database and TIMIT are used in these experiments. The results show that lack of enough speech resource that faces Arabic language can be solved by considering models' features of common phonemes given by English.