On Cognitive Translator
DOI:
https://doi.org/10.52340/lac.2026.11.25Keywords:
cognitive translatorAbstract
This is a research for creating a cognitive translator prototype based on brain electromagnetic activity, aiming to develop a cognitive translator prototype that uses brain activity to translate thoughts into different languages. The idea is to analyze linguistic activity data and develop algorithms to recognize and translate brain signals associated with specific concepts.
The main hypothesis is that the concept (or thought /whatever is to say/write) remains the same across languages haveing the different linguistic material for different langugaes. To test this hypothesis, we plan to record and analyze the neural activity of 90 participants speaking three different languages using EmoTV epoc - EEG (electroencephalography) technology.
The research involves several steps, including:
- Data collection: Recording EEG signals from participants as they think or speak in different languages.
- Data analysis: Analyzing the EEG signals using techniques such as FFT, PSD, ERP, and machine learning algorithms to identify patterns associated with specific concepts.
- Algorithm development: Developing algorithms to recognize and translate brain signals into different languages.
- Prototype development: Creating a software prototype of the cognitive translator.
The research aims to achieve several goals, including:
- Identifying the correlation between EEG signals and linguistic concepts
- Elaborating the neurological algorythms, which will connect the langugae concepts with the proper EEG sygnals.
- Recognizing pre-defined sentences with 70-90% accuracy based on brain activity
- Developing a software prototype of the cognitive translator
- Creating a scientifically grounded model for neural linguistic research
The research has the potential to revolutionize language technologies and establish a new research direction in Georgian/Kartvelian studies.
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References
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