In this paper, we show that linguistically motivated
pronunciation rules can improve phone
and word recognition results forModern Standard
Arabic (MSA). Using these rules and
the MADA morphological analysis and disambiguation
tool, multiple pronunciations per
word are automatically generated to build two
pronunciation dictionaries; one for training
and another for decoding. We demonstrate
that the use of these rules can significantly
improve both MSA phone recognition and
MSA word recognition accuracies over a baseline
system using pronunciation rules typically
employed in previous work onMSA Automatic
Speech Recognition (ASR). We obtain
a significant improvement in absolute accuracy
in phone recognition of 3.77%–7.29%
and a significant improvement of 4.1% in absolute
accuracy in ASR.