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Arnav Kapur is a computer scientist and engineer at MIT. He is known for his work and advocacy in developing AI systems that enhance and complement human abilities.
| This article may contain an excessive number of citations .(November 2023) |
Arnav Kapur is a computer scientist and engineer at MIT. He is known for his work and advocacy in developing AI systems that enhance and complement human abilities.
In 2016, Kapur worked at the Biomedical Cybernetics Laboratory at Harvard Medical School. While at Harvard, he showed that gene expression data in microarray and RNA-Seq experiments, could be considered approximately low-rank, which could then be used to reliably predict the data. [1] [2] [3] [4]
After this, Kapur attended Massachusetts Institute of Technology, working at the MIT Media Lab. [5] [6] [7] While at MIT, he developed a peripheral neural interface, dubbed AlterEgo, that recorded neuromuscular signals, sent from the brain to the various muscles of the speech system through subtle and voluntary stimulation, and transcribed them into basic speech commands. [5] [8] [9] [10] [11] This created a silent speech interface, having applications in facilitating speech for individuals who had lost the ability to communicate verbally. [12] [13] [14] [15] [16] [17] In 2018, Kapur in an interview with 60 Minutes, detailed the inner workings of the prototype and showcased a live demonstration. [18] [19] [20] [21] In 2019, Kapur gave a talk at TED, and demonstrated an updated version of the system. [22] [23] [24] [25] [26] He talked about how ethics can inform design and engineering as a principle [24] [27] [28] [29] [30] and advocated for technologies such as AI to be designed in a way that extended human capabilities. [29] [31] [32] [33]
Kapur has also exhibited artwork and AI tools that collaborate with human artists. [34] His work has been exhibited at alt.ai New York, Design Museum, Art Center Nabi. [35] [36] [37] [38] [39]
In 2020, Kapur featured on TIME magazine's 100 Best Inventions of 2020. [40] He has been awarded the Lemelson-MIT graduate prize. [41]
Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech. The reverse process is speech recognition.
The Lemelson–MIT Program awards several prizes yearly to inventors in the United States. The largest is the Lemelson–MIT Prize which was endowed in 1994 by Jerome H. Lemelson, funded by the Lemelson Foundation, and is administered through the School of Engineering at the Massachusetts Institute of Technology. The winner receives $500,000, making it the largest cash prize for invention in the U.S.
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Silent speech interface is a device that allows speech communication without using the sound made when people vocalize their speech sounds. As such it is a type of electronic lip reading. It works by the computer identifying the phonemes that an individual pronounces from nonauditory sources of information about their speech movements. These are then used to recreate the speech using speech synthesis.
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Ramesh Raskar is a Massachusetts Institute of Technology associate professor and head of the MIT Media Lab's Camera Culture research group. Previously he worked as a senior research scientist at Mitsubishi Electric Research Laboratories (MERL) during 2002 to 2008. He holds 132 patents in computer vision, computational health, sensors and imaging. He received the $500K Lemelson–MIT Prize in 2016. The prize money will be used for launching REDX.io, a group platform for co-innovation in Artificial Intelligence. He is well known for inventing EyeNetra, EyeCatra and EyeSelfie, Femto-photography and his TED talk for cameras to see around corners.
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The machine translation of sign languages has been possible, albeit in a limited fashion, since 1977. When a research project successfully matched English letters from a keyboard to ASL manual alphabet letters which were simulated on a robotic hand. These technologies translate signed languages into written or spoken language, and written or spoken language to sign language, without the use of a human interpreter. Sign languages possess different phonological features than spoken languages, which has created obstacles for developers. Developers use computer vision and machine learning to recognize specific phonological parameters and epentheses unique to sign languages, and speech recognition and natural language processing allow interactive communication between hearing and deaf people.
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AlterEgo is a wearable silent speech output-input device developed by MIT Media Lab. The device is attached around the head, neck, and jawline and translates your brain speech center impulse input into words on a computer, without vocalization.
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Live Transcribe is a smartphone application to get realtime captions developed by Google for the Android operating system. Development on the application began in partnership with Gallaudet University. It was publicly released as a free beta for Android 5.0+ on the Google Play Store on February 4, 2019. As of early 2023 it had been downloaded over 500 million times. The app can be installed from an .apk file by sideloading and it will launch, but the actual transcription functionality is disabled, requiring creation of an account with Google.
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