Unveiling Thoughts: A Review of Advancements in EEG Brain Signal Decoding into Text
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Abstract (arXiv)
The conversion of brain activity into text using electroencephalography (EEG) has gained significant traction in recent years. Many researchers are working to develop new models to decode EEG signals into text form. Although this area has shown promising developments, it still faces numerous challenges that necessitate further improvement. It's important to outline this area's recent developments and future research directions. In this review article, we thoroughly summarize the progress in EEG-to-text conversion. Firstly, we talk about how EEG-to-text technology has grown and what problems we still face. Secondly, we discuss existing techniques used in this field. This includes methods for collecting EEG data, the steps to process these signals, and the development of systems capable of translating these signals into coherent text. We conclude with potential future research directions, emphasizing the need for enhanced accuracy, reduced system constraints, and the exploration of novel applications across varied sectors. By addressing these aspects, this review aims to contribute to developing more accessible and effective Brain-Computer Interface (BCI) technology for a broader user base.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 14 of its 122 references that are in the map. First posted on arXiv 26 Apr 2024.
Builds on
14 of 122 references.
References · 14
- 2022Mind Reader: Reconstructing complex images from brain activitiescited by 85
- 2016Deep Learning Human Mind for Automated Visual Classificationcited by 76
- 2021Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classificationcited by 67
- 2019ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotationcited by 65
- 2018EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signalscited by 46
- 2015Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networkscited by 45
- 2015Transfer Learning in Brain-Computer Interfacescited by 39
- 2023DeWave: Discrete EEG Waves Encoding for Brain Dynamics to Text Translationcited by 36
- 2020Brain2Word: Decoding Brain Activity for Language Generationcited by 15
- 2022On The Effects Of Data Normalisation For Domain Adaptation On EEG Datacited by 13
- 2017Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG Signalscited by 11
- 2017Effective and Extensible Feature Extraction Method Using Genetic Algorithm-Based Frequency-Domain Feature Search for Epileptic EEG Multi-classificationcited by 3
2 more
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Citing papers per year: 2024: 1; 2025: 5; 2026: 4.
10 papers.
- 2025Learning Interpretable Representations Leads to Semantically Faithful EEG-to-Text Generationcited by 4
- 2025Foundation Models for Cross-Domain EEG Analysis Application: A Surveycited by 4
- 2025MEGConformer: Conformer-Based MEG Decoder for Robust Speech and Phoneme Classificationcited by 4
- 2025A Survey on Bridging EEG Signals and Generative AI: From Image and Text to Beyondcited by 3
- 2026ZUNA: Flexible EEG Superresolution with Position-Aware Diffusion Autoencoderscited by 3
- 2024How Many Bytes Can You Take Out Of Brain-To-Text Decoding?cited by 2
- 2025EEG-to-Text Translation: A Model for Deciphering Human Brain Activitycited by 0
- 2026LI-DSN: A Layer-wise Interactive Dual-Stream Network for EEG Decodingcited by 0
- 2026Structure-Guided Diffusion Model for EEG-Based Visual Cognition Reconstructioncited by 0
- 2026Is EEG-to-Text Feasible in Real-World Scenarios? An In-Depth Analysis Using a Neuropsychology-Inspired Benchmarkcited by 0
- 2026Is EEG-to-Text Feasible in Real-World Scenarios? An In-Depth Analysis Using a Neuropsychology-Inspired Benchmark21 Jul 2026
- 2026Structure-Guided Diffusion Model for EEG-Based Visual Cognition Reconstruction24 Apr 2026
- 2026LI-DSN: A Layer-wise Interactive Dual-Stream Network for EEG Decoding2 Apr 2026
- 2026ZUNA: Flexible EEG Superresolution with Position-Aware Diffusion Autoencoders9 Feb 2026
- 2025MEGConformer: Conformer-Based MEG Decoder for Robust Speech and Phoneme Classification1 Dec 2025
- 2025Foundation Models for Cross-Domain EEG Analysis Application: A Survey21 Aug 2025
- 2025Learning Interpretable Representations Leads to Semantically Faithful EEG-to-Text Generation21 May 2025
- 2025EEG-to-Text Translation: A Model for Deciphering Human Brain Activity20 May 2025
- 2025A Survey on Bridging EEG Signals and Generative AI: From Image and Text to Beyond17 Feb 2025
- 2024How Many Bytes Can You Take Out Of Brain-To-Text Decoding?22 May 2024