ISCA International Workshop on Speech and Language Technology in Education (SLaTE 2011)

Venice, Italy
August 24-26, 2011

Improving ASR Processing of Ungrammatical Utterances through Grammatical Error Modeling

Helmer Strik, Joost van Doremalen, Janneke van de Loo, Catia Cucchiarini

Centre for Language and Speech Technology, Radboud University, Nijmegen, The Netherlands

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

Full Paper

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.