Robust Feature Extraction to Utterance Fluctuation of Articulation Disorders Based on Random Projection
نویسندگان
چکیده
We investigated the speech recognition of a person with an articulation disorder resulting from the athetoid type of cerebral palsy. The articulation of the first speech tends to become unstable due to strain on speech-related muscles, and that causes degradation of speech recognition. In this paper, we introduce a robust feature extraction method based on PCA (Principal Component Analysis) and RP (Random Projection) for dysarthric speech recognition. PCA-based feature extraction performs reducing the influence of the unstable speaking style caused by the athetoid symptoms. Moreover, we investigate the feasibility of random projection for feature transformation in order to gain more performance in dysarthric speech recognition task. Its effectiveness is confirmed by word recognition experiments.
منابع مشابه
Integration of Metamodel and Acoustic Model for Dysarthric Speech Recognition
We investigated the speech recognition of a person with articulation disorders resulting from athetoid cerebral palsy. The articulation of the first words spoken tends to be unstable due to the strain placed on the speech-related muscles, and this causes degradation of speech recognition. Therefore, we proposed a robust feature extraction method based on PCA (Principal Component Analysis) inste...
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