In this paper we present a novel approach for a surface electromyographic speech recognition system based on sub-word units. Rather than using full word models as integrated in our previous work we propose here smaller sub-word units as prerequisites for large vocabulary speech recognition. This allows the recognition of words not seen in the training set based on seen sub-word units. Therefore we report on experiments with syllables and phonemes as sub-word units. We also developed a new feature extraction method that gains significant improvement for words and sub-word units. Index Terms: silent speech, non-audible speech recognition, electromyography, sub-word unit compariso
In our previous work, we reported a surface electromyographic (EMG) continuous speech recognition sy...
Sub-auditory speech recognition using electromyogram (EMG) sensors is potentially useful for interfa...
This paper presents results of electromyography (EMG) speech recognition which captures the electric...
A method for synthesizing speech from surface electromyogram (SEMG) signals in a frame-by-frame basi...
This paper discusses the use of surface electromyography for automatic speech recognition. Electromy...
Abstract—This paper presents the results of our research in silent speech recognition (SSR) using Su...
We report automatic speech recognition accuracy for individual words using eleven surface electromyo...
Speech is the natural medium of human communication, but audible speech can be overheard by bystande...
This research examines the evaluation of fSEMG (facial surface Electromyogram) for recognizing speec...
Abstract — This paper presents a silent-speech interface based on electromyographic (EMG) signals re...
For some time, new methods based on a different than acoustic signal analysis are used for speech re...
This thesis describes the implementation of an automatic speech recognition system based on surface ...
This paper presents a silent-speech interface based on electromyographic (EMG) signals recorded in t...
We present our recent advances in silent speech interfaces using electromyographic signals that capt...
Silent Speech Interfaces use data from the speech production process, such as visual information o...
In our previous work, we reported a surface electromyographic (EMG) continuous speech recognition sy...
Sub-auditory speech recognition using electromyogram (EMG) sensors is potentially useful for interfa...
This paper presents results of electromyography (EMG) speech recognition which captures the electric...
A method for synthesizing speech from surface electromyogram (SEMG) signals in a frame-by-frame basi...
This paper discusses the use of surface electromyography for automatic speech recognition. Electromy...
Abstract—This paper presents the results of our research in silent speech recognition (SSR) using Su...
We report automatic speech recognition accuracy for individual words using eleven surface electromyo...
Speech is the natural medium of human communication, but audible speech can be overheard by bystande...
This research examines the evaluation of fSEMG (facial surface Electromyogram) for recognizing speec...
Abstract — This paper presents a silent-speech interface based on electromyographic (EMG) signals re...
For some time, new methods based on a different than acoustic signal analysis are used for speech re...
This thesis describes the implementation of an automatic speech recognition system based on surface ...
This paper presents a silent-speech interface based on electromyographic (EMG) signals recorded in t...
We present our recent advances in silent speech interfaces using electromyographic signals that capt...
Silent Speech Interfaces use data from the speech production process, such as visual information o...
In our previous work, we reported a surface electromyographic (EMG) continuous speech recognition sy...
Sub-auditory speech recognition using electromyogram (EMG) sensors is potentially useful for interfa...
This paper presents results of electromyography (EMG) speech recognition which captures the electric...