  In this paper we demonstrate continuous noisy speech recognition using
connectionist temporal classification (CTC) model on limited Chinese vocabulary
using electroencephalography (EEG) features with no speech signal as input and
we further demonstrate single CTC model based continuous noisy speech
recognition on limited joint English and Chinese vocabulary using EEG features
with no speech signal as input. We demonstrate our results using various EEG
feature sets recently introduced in [1] as well as we propose a new deep
learning architecture in this paper which can perform continuous speech
recognition using raw EEG signals on limited joint English and Chinese
vocabulary.
