Graphene-Based Sensors Developed for Speech Recognition CellRepPhysSci speech graphene sensors
By Bhavna KavetiOct 12 2022Reviewed by Susha Cheriyedath, M.Sc. Despite the progress in technology and exploitation of automatic speech recognition, technological barriers to flexible solutions and user satisfaction still exist under certain circumstances. These barriers are related to several factors, such as sensitivity to the environment , speech disorders, and limited privacy.
Human-Computer Interactions with Speech-Recognition System Human-computer interaction is a primary issue in the information technology era. Hence, designing a convenient and user-friendly interface has become a critical technological issue. Machine-dependent interfaces limit the use of computers in most populations. Speech enables a suitable form of communication for human-machine interaction.
Acquiring a high identification rate for EEG data is challenging because of its low signal-to-noise ratio . While acquiring higher identification is possible with ECoG signals, this technique requires intracranial insertion of electrodes. Silent speech recognition based on electromyographic signals can achieve greater accuracy. However, better accuracy necessitates the installation of eight electrodes on the human skin, thereby substantially reducing its wearability.
Surface electrophysiology electrodes may transform these ion currents into electron currents, which are then employed as electromyographic signals to represent the strength of the muscle contraction. Consequently, the surface of the skin could be distorted by muscular contraction. Furthermore, the chin and throat have several overlapping muscles; therefore, the acquired electromyographic signals usually include action potentials from various muscle fibers. Thus, the underlying speech-related elements were analyzed in the signal rather than trying to determine the source of muscle movements.
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