ArticleSensors (Basel, Switzerland)2021
Silent EEG-Speech Recognition Using Convolutional and Recurrent Neural Network with 85% Accuracy of 9 Words Classification.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence for brain-to-speech decoding in paralysis: a systematic review.BMC medical informatics and decision making · 2026Pooled it
- Systematic Review of EEG-Based Imagined Speech Classification Methods.Sensors (Basel, Switzerland) · 2024Pooled it
- DiagPat: An Explainable Language Detection Model Using EEG Signals.Sensors (Basel, Switzerland) · 2026Article
- Soft Multiaxial Strain Mapping Interface with AI-Driven Decoding for Silent Speech in Noise.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- ThinkSTra: a transformer-driven architecture for decoding imagined speech from EEG with spatial-temporal dynamics.Medical & biological engineering & computing · 2025Article
- Mapping EEG Metrics to Human Affective and Cognitive Models: An Interdisciplinary Scoping Review from a Cognitive Neuroscience Perspective.Biomimetics (Basel, Switzerland) · 2025Review
- Sentence-Level Silent Speech Recognition Using a Wearable EMG/EEG Sensor System with AI-Driven Sensor Fusion and Language Model.Sensors (Basel, Switzerland) · 2025Article
- From pronounced to imagined: improving speech decoding with multi-condition EEG data.Frontiers in neuroinformatics · 2025Article
- Neural signals, machine learning, and the future of inner speech recognition.Frontiers in human neuroscience · 2025Review
- tDCS and neurofeedback in ADHD treatment.Frontiers in systems neuroscience · 2025Review
- Advances in brain-computer interface for decoding speech imagery from EEG signals: a systematic review.Cognitive neurodynamics · 2024Review
- Lobish: Symbolic Language for Interpreting Electroencephalogram Signals in Language Detection Using Channel-Based Transformation and Pattern.Diagnostics (Basel, Switzerland) · 2024Article
- Exploring Convolutional Neural Network Architectures for EEG Feature Extraction.Sensors (Basel, Switzerland) · 2024Article
- Machine-Learning Methods for Speech and Handwriting Detection Using Neural Signals: A Review.Sensors (Basel, Switzerland) · 2023Review
- Survey on the research direction of EEG-based signal processing.Frontiers in neuroscience · 2023Review
- CNN Architectures and Feature Extraction Methods for EEG Imaginary Speech Recognition.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this work, we focus on silent speech recognition in electroencephalography (EEG) data of healthy individuals to advance brain-computer interface (BCI) development to include people with neurodegeneration and movement and communication difficulties in society. Our dataset was recorded from 270 healthy subjects during silent speech of eight different Russia words (commands): 'forward', 'backward', 'up', 'down', 'help', 'take', 'stop', and 'release', and one pseudoword. We began by demonstrating that silent word distributions can be very close statistically and that there are words describing directed movements that share similar patterns of brain activity. However, after training one individual, we achieved 85% accuracy performing 9 words (including pseudoword) classification and 88% accuracy on binary classification on average. We show that a smaller dataset collected on one participant allows for building a more accurate classifier for a given subject than a larger dataset collected on a group of people. At the same time, we show that the learning outcomes on a limited sample of EEG-data are transferable to the general population. Thus, we demonstrate the possibility of using selected command-words to create an EEG-based input device for people on whom the neural network classifier has not been trained, which is particularly important for people with disabilities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.