# Relating the Neural Representations of Vocalized, Mimed, and Imagined Speech

arXiv: https://arxiv.org/abs/2602.22597 · HTML: https://mlsanity.com/paper/2602.22597/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Feb 2026.

## Built on by (most cited first, 2 of 2)

- [Zero-Shot Imagined Speech Decoding via Imagined-to-Listened MEG Mapping](https://mlsanity.com/paper/2605.08075/) (2026)
- [Mechanistic Interpretability Reveals Shared Causal Subspaces in Brain-to-Speech Decoders](https://mlsanity.com/paper/2609.31992/) (2026)

## Abstract (arXiv)

We investigated the relationship among neural representations of vocalized, mimed, and imagined speech recorded using publicly available stereotactic EEG recordings. Most prior studies have focused on decoding speech responses within each condition separately. Here, instead, we explore how responses across conditions relate by training linear spectrogram reconstruction models for each condition and evaluate their generalization across conditions. We demonstrate that linear decoders trained on one condition generally transfer successfully to others, implying shared speech representations. This commonality was assessed with stimulus-level discriminability by performing a rank-based analysis demonstrating preservation of stimulus-specific structure in both within- and across-conditions. Finally, we compared linear reconstructions to those from a nonlinear neural network. While both exhibited cross-condition transfer, linear models achieve superior stimulus-level discriminability.