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Several adaptation approaches have heen proposed in an effort t,o improve the speech recognition performance in mismatched conditions. However, the application of these approaches had heen most,ly constrained to the speaker or channel adaptation tasks. In this paper, we first investigate t,he effect of mismatched dialects between training and testing speakers in an Automatic Speech Recognition (ASR) system. We find that a mismatch in dialect,s significantly influences the recognition accuracy. Consequently, we apply several adaptation approaches to develop a dialect-specific recognition system using a dialect-dependent, system trained on a different dialect and a small number of training sentences from the target dialect. We show that, adaptation improves recognition performance dramatically with small amount,s of training sentences. We further show that, although the recognition performance of traditionally trained systems highly degrades as we decrease the number of training speakers, the performance of adapted systsems is not influenced so much.

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