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- W3135185408 abstract "We introduce a spatial artifact detection method for a surface electromyography (EMG) based speech recognitionsystem. The EMG signals are recorded using grid-shaped electrode arrays affixed to the speakersface. Continuous speech recognition is performed on the basis of these signals. As the EMG data are highdimensional,Independent Component Analysis (ICA) can be applied to separate artifact components from thecontent-bearing signal. The proposed artifact detection method classifies the ICA components by their spatialshape, which is analyzed using the spectra of the spatial patterns of the independent components. Componentsidentified as artifacts can then be removed. Our artifact detection method reduces the word error rates (WER)of the recognizer significantly. We observe a slight advantage in terms of WER over the temporal signal basedartifact detection method by (Wand et al., 2013a)." @default.
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- W3135185408 date "2014-01-01" @default.
- W3135185408 modified "2023-09-26" @default.
- W3135185408 title "Spatial Artifact Detection for Multi-channel EMG-based Speech Recognition" @default.
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- W3135185408 doi "https://doi.org/10.5220/0004793901890196" @default.
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