Advancements in Subvocal Recognition

Brain-Computer Interface (BCI) systems and research projects that have explored or achieved advancements in subvocal recognition:

1. AlterEgo:
   • Developed by MIT Media Lab, AlterEgo uses EMG signals to detect subvocalized speech for hands-free interaction with devices.
2. Subvocal Speech Recognition System (SSRS):
   • Developed by NASA’s Jet Propulsion Laboratory (JPL), SSRS focuses on using EMG signals from the throat for subvocalization recognition.
3. MindAffect:
   • A BCI system integrating EEG signals with deep learning models, initially focused on augmentative and alternative communication (AAC) for individuals with motor disabilities, including potential for subvocalization recognition.
4. BrainGate:
   • The BrainGate Neural Interface System from Brown University aims to restore communication and control for individuals with paralysis, with potential for subvocal recognition.
5. University of California, San Francisco (UCSF) BCI Research:
   • UCSF researchers have been exploring BCI systems that decode neural activity related to speech planning and production, including subvocalization.
6. Cognitive Architecture for Cognitive Systems (CogArch):
   • CogArch is an interdisciplinary research project exploring cognitive architectures and could contribute to advanced BCI systems, potentially including subvocal recognition.
7. Brain-Computer Interfacing and Neurorehabilitation Lab (BCI-NRL):
   • BCI-NRL focuses on BCI technologies for communication and neurorehabilitation, with potential applications in subvocalization recognition.
8. Neurable:
   • Neurable is a company working on BCI technologies for various applications, including communication, gaming, and virtual reality, with potential for subvocal recognition capabilities.
9. Neurable Mind:
   • Another project by Neurable, Neurable Mind, explores BCI systems for real-time interaction and control using EEG signals, which could extend to subvocalization recognition.
10. Brain-Machine Interface (BMI) Laboratory, University of Pittsburgh:
    • The BMI Lab at the University of Pittsburgh has been involved in BCI research, including studies on decoding neural signals related to speech and potential applications in subvocal recognition.

These projects and research efforts represent a subset of the ongoing work in the field of subvocal recognition and BCI technologies, highlighting diverse approaches and applications aimed at decoding internal speech signals for communication and control purposes.