AI speech synthesis system

AI Speech Synthesis System

In a groundbreaking development, researchers at New York University (NYU) have built an innovative AI system that translates brain signals into speech. This ambitious project leverages electrocorticography (EOG) signals and sophisticated deep learning models to convert brain activity into speech features such as pitch and loudness. The result is an audible spectrogram that translates into natural-sounding speech.

During the study, 48 participants undergoing epilepsy surgery read sentences while the AI-generated speech closely mimicked their original speech patterns. This new technology holds promise for revolutionizing communication for individuals with speech impairments.

Keywords

• AI
• Speech synthesis
• New York University
• Brain signals
• Electrocorticography (EOG)
• Deep learning
• Epilepsy surgery
• Speech features
• Spectrogram

FAQ

Q: What is the primary achievement of the NYU researchers?
A: The primary achievement is the development of an AI system that translates brain signals into natural-sounding speech.

Q: What technology does the AI system use to capture brain activity?
A: The system uses electrocorticography (EOG) signals to capture brain activity.

Q: How does the AI system process brain signals into speech?
A: The system uses a deep learning model to accurately convert brain activity into speech features like pitch and loudness, leading to the creation of an audible spectrogram.

Q: Who were the participants in the study?
A: The study involved 48 participants who were undergoing epilepsy surgery.

Q: How accurate was the AI-generated speech in comparison to the original speech?
A: The AI-generated speech closely matched the original speech read by the participants.