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Home National Education

IIT-M develops AI technology to convert Brain signals of Speech-Impaired Humans into English Language

The other major application of this field of research is that it can be used to interpret nature’s signals such as plant photosynthesis process or their response to external forces. This will help in predicting monsoons, earthquake, floods, Tsunami and other natural disasters using our Artificial Intelligence and Deep Learning algorithms

by NavJeevan
5 years ago
in Education, Health & Environment, Science and Technology, Student's Corner, Youth
Reading Time: 2 mins read
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IIT-M develops AI technology to convert Brain signals of Speech-Impaired Humans into English Language

The research team of IIT-M developing an Artificial Intelligence (AI) technology to convert brain signals of speech impaired humans into English Language. NE PHOTO

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NE SCIENCE & TECHNOLOGY BUREAU
CHENNAI, FEB 4

Researchers of IIT-M have developed an Artificial Intelligence (AI) technology to convert brain signals of speech impaired humans into English Language. The other major application for this field of research is that the researchers can potentially interpret nature’s signals such as like plant photosynthesis process or their response to external forces.

According IIT-M release, a team of researchers lead by Dr. Vishal Nandigana, Assistant Professor, Fluid Systems Laboratory, Department of Mechanical Engineering, IIT Madras, is working on this area of research.

Electrical signals, brain signal or any signal, in general, are waveforms which are decoded to meaningful information using physical law or mathematical transforms such as Fourier Transform or Laplace Transform. These physical laws and mathematical transforms are science-based languages discovered by renowned scientists such as Sir Isaac Newton and Jean-Baptiste Joseph Fourier.

Elaborating on this Research, Dr. Vishal Nandigana, the lead researcher, said, “The output result is the ionic current, which represents the flow of ions which are charged particles. These electrically driven ionic current signals are worked on to be interpreted as human language meaning speech. This would tell us what the ions are trying to communicate with us. When we succeed with this effort, we will get electrophysiological data from the neurologists to get brain signals of speech impaired humans to know what they are trying to communicate.”

Further, Dr. Vishal Nandigana said, “The other major application of this field of research we see potentially is, can we interpret nature’s signals, like plant photosynthesis process or their response to external forces mean when we collect their real data signal. The data signal also, we believe, is going to be in some wave like pattern with spikes, humps and crusts. So the big breakthrough will be, we can interpret what plants and nature is trying to communicate to us. This will help in predicting monsoons, earthquake, floods, Tsunami and other natural disasters using our Artificial Intelligence and Deep Learning algorithms. If we understand the nature signals better we can take care of it well is our objective that we want to pitch in from our laboratory.”

IIT Madras Researchers are working on how these real data signal can be decoded into human language such as English language and if the real data signal can be interpreted as a simple human language that all human beings can understand.

`Brain signals are typical electrical signals’

Brain signals are typically electrical signals. These are wave like patterns with spikes, humps and crusts which can be converted into simple human language meaning speech using Artificial Intelligence and Deep Learning algorithms. This enabled the Researchers to read direct electrical signals of the brain.

The researchers tested this concept by getting experimental electrical signals through experiments in the laboratory to get signals from nanofluidic transport inside nanopores. The nanopores were filled with saline solution and mediated using an electric field, the release added.

Tags: aitechnologybrainconvertdevelopsiit-mintosignalsspeechto
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