Paper: Corrective Models For Speech Recognition Of Inflected Languages

ACL ID W06-1646
Title Corrective Models For Speech Recognition Of Inflected Languages
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2006
Authors

This paper presents a corrective model for speech recognition of inflected lan- guages. The model, based on a discrim- inative framework, incorporates word n- grams features as well as factored mor- phological features, providing error reduc- tion over the model based solely on word n-gram features. Experiments on a large vocabulary task, namely the Czech portion of the MALACH corpus, demonstrate per- formance gain of about 1.1–1.5% absolute in word error rate, wherein morphologi- cal features contribute about a third of the improvement. A simple feature selection mechanism based on χ2 statistics is shown to be effective in reducing the number of features by about 70% without any loss in performance, making it feasible to explore yet larger feature spaces.