Speech decoding: from neural signals to practical communication

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Speech is a fundamental aspect of human interaction, shaping how we connect, learn, and engage with society. Neurological injuries or diseases can impair speech, leading to significant social and psychological challenges. Recent advancements in brain-computer interface (BCI) technology have enabled significant progress in decoding speech directly from neural signals. This breakthrough represents a promising opportunity to restore communication for those who have lost their ability to speak. Speech decoding combines neuroscience, engineering, machine learning, linguistics, and clinical innovation, enabling the extraction of phonemes, words, or continuous speech from neural recordings. This progress not only holds potential for assistive communication tools but also enhances our understanding of language production and perception.

This Research Topic aims to advance the science and technology of speech decoding by collecting articles that span from foundational research to translational applications. We encourage contributions from interdisciplinary researchers working at the intersection of neural decoding, speech science, artificial intelligence, and clinical practice. The primary goal is to foster innovation that leads to practical communication solutions for individuals with speech impairments.

To gather further insights into speech decoding, we welcome articles addressing, but not limited to, the following themes:

Neural decoding studies extracting language elements from brain activity

Algorithmic advancements for real-time speech decoding from neural data

Investigations into the neural representation of speech features

Neuroethics and user-centered design for neural speech systems

Multilingual and cross-population perspectives in speech decoding

Interdisciplinary work integrating insights from various related fields

Complexity Studies of Different Neural Speech Approaches

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

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Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: speech, BCI, neural signals, speech decoding, machine learning

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.