# BINGO cross-linguistic inner-speech dataset: EEG decoding results

Inner speech of 15 matched nouns in Greek and in English, across people and languages

The cross-linguistic inner-speech dataset of the BINGO (Brain Imagined-Speech Communication) project at CERTH is one of the two EEG datasets the project releases on its website. On each trial a participant saw one of 15 matched nouns, in Greek or in English, held it in memory through a countdown, and then said it silently during a 1.5-second inner-speech window; each item was repeated ten times, in fully randomised order. The project's public deliverable D3.1 describes the protocol and states that the same preprocessing, including artifact removal, was applied to both released datasets. The source states no licence. Only its complete subject records are used here.

**Also known as** BINGO (Brain Imagined-Speech Communication) · BINGO cross-linguistic inner speech elicitation dataset · BINGO Dataset 2 · D3.1 – The BINGO Benchmarking Framework

Description sources [bingo-project.gr](https://bingo-project.gr/datasets/) · [bingo-project.gr](https://bingo-project.gr/download/397)

## Where it appears

- [What can a small pilot show, and what can it not?](https://bci.report/topics/pilot-studies/#bingo)

## Published results

Every figure below is copied from a reviewed download, not recomputed for this page.

### Pilot studies · inner speech in Greek and English, across people and across languages (a negative result)

Read with its protocol: [Pilot studies](https://bci.report/topics/pilot-studies/#bingo) · Chance level 6.7% · [pilot-studies-update.json](https://bci.report/data/pilot-studies-update.json)

**Balanced accuracy, 4 configurations.** Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

- Relative band power + ridge classifier · Trained on Greek, tested on Greek · a subject field left out: 6.4% (5.8%–6.9%)
- Relative band power + ridge classifier · Trained on Greek, tested on English · a subject field left out: 6.6% (5.5%–7.6%)
- Relative band power + ridge classifier · Trained on English, tested on English · a subject field left out: 6.7% (5.8%–7.6%)
- Relative band power + ridge classifier · Trained on English, tested on Greek · a subject field left out: 7.1% (6.2%–7.9%)

| Method | Condition | Metric | Value | People |
| --- | --- | --- | --- | --- |
| Relative band power + ridge classifier | Trained on Greek, tested on Greek · a subject field left out | Balanced accuracy | 6.4% (5.8%–6.9%) — Top-3 accuracy 19.1%, against its prior of 20.0%. | 17 subject fields as the source defines them, not proven distinct people |
| Relative band power + ridge classifier | Trained on Greek, tested on English · a subject field left out | Balanced accuracy | 6.6% (5.5%–7.6%) — Top-3 accuracy 21.0%, against its prior of 20.0%. | 17 subject fields as the source defines them, not proven distinct people |
| Relative band power + ridge classifier | Trained on English, tested on English · a subject field left out | Balanced accuracy | 6.7% (5.8%–7.6%) — Top-3 accuracy 19.9%, against its prior of 20.0%. | 17 subject fields as the source defines them, not proven distinct people |
| Relative band power + ridge classifier | Trained on English, tested on Greek · a subject field left out | Balanced accuracy | 7.1% (6.2%–7.9%) — Top-3 accuracy 19.6%, against its prior of 20.0%. | 17 subject fields as the source defines them, not proven distinct people |
| Relative band power + ridge classifier | Across languages minus within, the mean over both training languages | Paired difference | +0.3 pp (−0.6–+1.3 pp) — The interval spans zero: no superiority or equivalence between languages, and no significance test. | 17 subject fields as the source defines them, not proven distinct people |

Every direction is close to the 15-class prior. A negative result for this one baseline in this setting: it does not show that inner speech cannot be decoded by other methods. The intervals are approximate and descriptive, from overlapping leave-one-field-out fits. Outside every leaderboard and model ranking.

Delivered signals, as the project describes them (BINGO deliverable D3.1, version 2.0): the same preprocessing for both of its released datasets — band-pass and notch filtering, Artifact Subspace Reconstruction (ASR) and FORCe removal of ocular and muscle artifacts — and then segmentation into trials. The signals analysed here were therefore artifact-cleaned on the continuous recordings before any trial was cut. As the project states it; not re-verified against the delivered file.

## Source and licence

### BINGO cross-linguistic inner-speech dataset

**Credit** BINGO (Brain Imagined-Speech Communication) project, CERTH · cross-linguistic inner-speech EEG dataset, https://bingo-project.gr/datasets/; no licence is stated by the source. Documentation: Fotis P. Kalaganis, Kostas Georgiadis, Maria Kyrou, Spiros Nikolopoulos and Ioannis Kompatsiaris, D3.1 – The BINGO Benchmarking Framework, version 2.0, public deliverable (2025), https://bingo-project.gr/download/397. Derived analysis by BCI Report; not endorsed by the authors.

No licence stated · [Dataset record ↗](https://bingo-project.gr/datasets/)

BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report from data whose source states no licence; no right to reuse the data is implied.

### Ethics and consent, as the source states them

Ethics approval: No ethics-approval reference is published by the source.

Informed consent: The project’s public deliverable D3.1, version 3.0, states that each participant signed a consent form before the sessions. It says so for the project’s 20-participant NATO-alphabet dataset, recorded in the same CERTH laboratory; the cross-language dataset’s own documentation, D3.1 version 2.0, has no ethics or consent statement.

The owner decided to publish these aggregates on that basis. Consent statement read from [D3.1 – The BINGO Benchmarking Framework, version 3.0 ↗](https://bingo-project.gr/download/402). [BINGO’s rights on the data-use page →](https://bci.report/data-use/#bingo-rights)

[All datasets →](https://bci.report/datasets/) · [All methods →](https://bci.report/methods/)

## Cite this page

BCI Report (2026). *BINGO cross-linguistic inner-speech dataset: EEG decoding results*. https://bci.report/datasets/bingo-imagined-speech/

Figures from release [`pilot-studies-update-20261012`](https://bci.report/releases/#pilot-studies-update-20261012) (2026-10-12). Cite the upstream dataset as well: its credit is on this page.

Every release is archived on Zenodo: [doi:10.5281/zenodo.23123296](https://doi.org/10.5281/zenodo.23123296). [BibTeX for the site and its releases →](https://bci.report/api/#cite-heading) · [CITATION.cff ↗](https://raw.githubusercontent.com/twu3202/bci-report/main/CITATION.cff)

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Markdown copy of https://bci.report/datasets/bingo-imagined-speech/, generated from the published page. Figures are aggregate results; terms of use: https://bci.report/data-use/