Bilingual and dialectal adaptation and retraining

In this paper, we report our investigations on the use of adaptation and retraining in our bilingual (Italian, German) and multidialectal recognition system. Our approach for bilingual speech recognition is to assume the two languages as being one, which is best suited for a task where Italian and German natives speak both languages, resulting in a variety of accents and dialects. We performed adaptation on single speakers and speaker groups built from combinations of spoken and native language. Furthermore, we performed retraining on partitions of the adaptation or training data. Our experiments led to an error rate reduction in all cases: compared to the baseline system, we achieved an overall improvement of 14, 12–14 and 7 % for speaker adaptation, speaker group adaptation and retraining, respectively. Furthermore, we found among others that performance is rather stable for Italian between adaptation and retraining, while adaptation for German outperforms retraining by far.