Speech Recognition With No Speech Or With Noisy Speech Beyond English
arXiv:1906.08045
Abstract
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.
arXiv commentarXiv admin note: text overlap with arXiv:1906.08871
References in corpus (5)
- Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
- Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
- Attention-Based Models for Speech Recognition
- State-of-the-art Speech Recognition using EEG and Towards Decoding of Speech Spectrum From EEG
- Simulation Experiment of BCI Based on Imagined Speech EEG Decoding