Continuous Speech Recognition using EEG and Video

--In this paper we investigate whether electroen-cephalography (EEG) features can be used to improve the performance of continuous visual speech recognition systems. We implemented a connectionist temporal classification (CTC) based end-to-end automatic speech recognition (ASR) model for performing recognition. Our results demonstrate that EEG features are helpful in enhancing the performance of continuous visual speech recognition systems. In recent years there has been lot of interesting work done in the fields of lip reading and audio visual speech recognition. In [1] authors demonstrated end-to-end sentence level lip reading and in [2] authors demonstrated deep learning based end-to- end audio visual speech recognition.