Maitreyee Wairagkar

Human-calibrated automated intelligibility evaluation of speech neuroprostheses

This paper fine-tunes an ASR model on human-transcribed synthesized speech to better align its word error rate with human perception, achieving higher correlation than zero-shot ASR.

A generalizable speech neuroprosthesis

This paper introduces a multi-user transformer-based decoder for intracortical speech BCIs, achieving lower word error rates with less training data than individual models.

Brain2voice 2.0: High-performance voice synthesis brain-computer interface

Brain2voice 2.0 improves voice synthesis from neural signals, achieving 5.24% word error rate, 8x better than prior methods, enabling real-time intelligible speech for paralyzed individuals.

Long-term independent use of an intracortical brain-computer interface for speech and cursor control

A paralyzed man with ALS used a long-term intracortical BCI for over two years to communicate, control a computer, and work independently.

Neural decoding of speech using deep neural ensembles

This paper tests deep neural ensembles in real-time speech BCIs, showing reduced word error rates and introducing a computationally efficient pseudoensembling method.

Premotor cortex uses a compositional neural geometry to plan words

The paper shows that premotor cortex uses a compositional neural geometry to plan words by combining phoneme representations, enabling efficient planning of novel sequences.

Encoding of speech modes and loudness in ventral precentral gyrus

This study decodes speech mode and loudness from ventral precentral gyrus activity in two participants, achieving high accuracy in predicting speech parameters and developing a closed-loop decoder for expressive speech neuroprostheses.

Cross-brain transfer of high-performance intracortical speech and handwriting BCIs

This paper demonstrates cross-brain transfer learning for intracortical BCIs decoding speech and handwriting, showing improved performance with limited training data and specific decoder design.

Decoding intended speech with an intracortical brain-computer interface in a person with longstanding anarthria and locked-in syndrome

This paper decodes intended speech from a person with anarthria and locked-in syndrome using an intracortical brain-computer interface, showing that phonemes, words, and higher-order language units can be decoded above chance.

An instantaneous voice synthesis neuroprosthesis

This paper demonstrates a brain-to-voice neuroprosthesis that synthesizes speech from neural activity, enabling real-time voice modulation with closed-loop feedback.

Error encoding in human speech motor cortex

The paper shows error detection signals in speech motor cortex during neuroprosthesis use, enabling error identification with 86% accuracy and revealing distinct patterns for different error types.

Speech motor cortex enables BCI cursor control and click

This paper demonstrates that neural activity from ventral motor cortex can enable high-performance cursor control and click for brain-computer interfaces.

A mosaic of whole-body representations in human motor cortex

The paper maps human motor cortex using microelectrode recordings, finding whole-body representations and challenging the traditional motor homunculus model.