ISCA International Workshop on Speech and Language Technology in Education (SLaTE 2011)
Automatic speech recognition (ASR) of non-native utterances
with grammatical errors is problematic. A new method which
makes it possible to better recognize such utterances is
presented in the current paper. It can be briefly summarized as
follows: extract error patterns automatically from a learner
corpus, formulate rewrite rules for these syntactic and
morphological errors, build finite state grammars (FSGs), and
use these FSGs as language models in ASR systems. All rules
used in isolation and in different combinations yield lower
word error rates (WERs).
Index Terms. computer-assisted language learning (CALL), non-native speech, grammatical errors, automatic speech recognition (ASR), language modeling
Bibliographic reference. Strik, Helmer / Doremalen, Joost van / Loo, Janneke van de / Cucchiarini, Catia (2011): "Improving ASR processing of ungrammatical utterances through grammatical error modeling", In SLaTE-2011, 109-112.