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How large an effect would we have seen? Positive controls, detection floors and dataset pitfalls in scalp-EEG speech decoding

Blessing ADEIKA, Onyema Osuagwu · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.20942 · cited by 0 works (OpenAlex) · open-access PDF

Korean

이 연구는 일반적으로 긍정적 인 통제, 일반적으로 공개 연설을 통해 그들의 파이프라인을 검증하고, 공공 연설 준비를 설명하지 않고 긍정적 인 효과 크기의 파이프라인이 감지 할 수있는 결과를 보고합니다. 접근 방식. ds003626 (소리로 생각), KaraOne 및 2020 국제 뇌 - 컴퓨터 인터페이스 경쟁의 트랙 3을 사용하여 시험 표지판의 디코딩 및 시험 선택을 사용합니다. 2020 국제 뇌 - 컴퓨터 인터페이스 경쟁의 KaraOne 및 트랙 3을 사용하여, 우리는 오버트 연설의 디코딩을 검사하고, 파이프라인이 감지 할 수있는 아르티팩트 채널 하위 세트, 밴드 제한된 디코딩 및 시험 표지판 선택을 사용하여, 우리는 5 개의 조

Machine translation (Meta M2M100); the English original follows.

Abstract

Objective. Studies that decode imagined speech from scalp electroencephalography (EEG) commonly validate their pipelines with a positive control, usually overt speech, and report null results without stating what effect size the pipeline could have detected. Approach. Using ds003626 ("Thinking out loud"), KaraOne and Track 3 of the 2020 International Brain-Computer Interface Competition, we audited decoding of overt speech, articulator preparation and imagined speech with artifact-channel subsets, band-limited decoding and trial selection, under a protocol that enforces split integrity by assertion. We injected class-dependent effects of known amplitude into the real recordings to measure the detection floor of five decoder families, and we checked the ds003626 labels against the dataset's acquisition protocol. Main results. On ds003626, two lip electrodes decoded overt speech at 0.7430 and the eight external channels at 0.7068, against 0.4231 for the 128-channel scalp montage, and no decodable signal survived in the 8-30 Hz band. On the other two corpora, within-subject accuracy rose monotonically with frequency into the range dominated by muscle activity. Band-power logistic regression detected an injected 8-30 Hz desynchronization of 0.54 uV under a criterion fixed in advance, whereas a compact convolutional network (EEGNet) detected nothing within subject up to 4.31 uV. In ds003626, the condition codes are the reverse of the intuitive reading, the class encoding changed between public releases, and condition is a deterministic function of time within each session. Significance. In these corpora the overt-speech positive control is dominated by myogenic signal and cannot validate a decoding pipeline. We recommend that speech-decoding studies report band-limited and artifact-channel accuracy, the direction of accuracy across frequency, and a measured detection floor.

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Topics: Decoding methods, Speech recognition, Computer science, SIGNAL (programming language), Pipeline (software), Encoding (memory)

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