We will study promising modeling techniques to develop ASR systems in languages for which large amounts of training data are not available. We intend to pursue three themes. The first concerns the development of algorithms to map pronunciation dictionary entries in the target language to elements in the dictionaries of the source languages. The third theme will be development of clustering and adaptation techniques to train a single set of acoustic models using data pooled from the available source languages. The best data for this modeling task would be natural, unscripted speech collected on a quiet, wide-band acoustic channel.
News broadcasts are a good source of such speech and are fairly easily obtained.
Broadcast news data of other source or target languages, possibly German or Russian, will be used if they become available in a suitable amount and quality.