Cross-lingual pronunciation modelling for indonesian speech recognition

The resources necessary to produce Automatic Speech Recognition systems for a new language are considerable, and for many languages these resources are not available. This emphasizes the need for the development of generic techniques which overcome this data shortage. Indonesian is one language which suffers from this problem and whose population and importance suggest it could benefit from speech enabled technology. Accordingly, we investigate using English acoustic models to recognize Indonesian speech. The mapping process, where the symbolic representation of the Source language acoustic models is equated to the Target language phonetic units, has typically been achieved using one to one mapping techniques. This mapping method does not allow for the incorporation of predictable allophonic variation in the lexicon. Accordingly, in this paper we present the use of cross-lingual pronunciation modelling to extract context dependant mapping rules, which are subsequently used to produce a more accurate cross lingual lexicon.