Wednesday March 20, 2019
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Thanks To Artificial Intelligence, Radio Journalist Regains His Voice

The AI system slices each word read out by an individual into 100 tiny pieces

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The AI-based system named "Philyra" can learn about perfume formulas, raw materials, historical success data and industry trends. Pixabay

A US radio journalist who had lost his voice two years ago due to a rare neurological condition has regained the ability to speak, thanks to artificial intelligence (AI), the media reported.

Jamie Dupree, 54, a political radio journalist with Cox Media Group, got a new voice that trained a neural network to predict how he would talk, using samples from his old voice recordings, the BBC reported.

With his new voice, Dupree can now write a script and then use a free text-to-speech software programme called Balabolka on his laptop to turn it into an audio recording.

If a word or turn of phrase does not sound quite right in the recording, he can slow certain consonants or vowels down, or swap a word to one that does work, or change the pitch, and he can have a full radio story ready to go live in just seven minutes.

“This has saved my job and saved my family from a terrible financial unknown,” Dupree was quoted as saying to the BBC.

In 2016, Dupree was diagnosed with tongue protrusion dystonia — a rare neurological condition where the tongue pushes forward out of his mouth and his throat tightens whenever he wants to speak, making it impossible for him to say more than two or three words at a time.

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artificial intelligence, brain, Pixabay

Thanks to the new computer-generated voice, created for him by Scottish technology company CereProc, Dupree is set to come back on air, the report said.

The AI system slices each word read out by an individual into 100 tiny pieces, and does this with lots of common words until eventually it understands how basic phonetics work in that person’s voice and has an ordered sequence for all the pieces in each word.

Then, the neural network can create its own sounds and predict what the person would sound like if they were to say a series of words in conversation.

Also read: This Way China Can Help India In The Terms of Artificial Intelligence

“AI techniques work quite well on small constrained problems, and learning to model speech is something deep neural nets can do really well,” Chris Pidcock, CereProc’s chief technical officer and co-founder, told the BBC. (IANS)

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Google Claims Eye Doctors Can Turn More Effective Using AI

Without assistance, general ophthalmologists are significantly less accurate than the algorithm, while retina specialists are not significantly more accurate than the algorithm. 

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The research team at Google AI believes that some of these pitfalls may be avoided if the computer can "explain" its predictions. Pixabay

As Artificial Intelligence (AI) continues to evolve, diagnosing diseases has become faster with greater accuracy. A new study from the Google AI research group shows that physicians and algorithms working together are more effective than either one alone.

In the study, to be published in the journal Ophthalmology, the researchers created a system which not only improved the ophthalmologists’ diagnostic accuracy but also improved the algorithm’s accuracy.

The study expands on previous work from Google AI showing that its algorithm works roughly as well as human experts in screening patients for a common diabetic eye disease called diabetic retinopathy.

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To test this theory, ten ophthalmologists (four general ophthalmologists, one trained outside the US, four retina specialists, and one retina specialist in training) were asked to read images with and without algorithm assistance. Pixabay

“What we found is that AI can do more than simply automate eye screening, it can assist physicians in more accurately diagnosing diabetic retinopathy. AI and physicians working together can be more accurate than either one alone,” said lead researcher Rory Sayres.

Recent advances in AI promise to improve access to diabetic retinopathy screening and to improve its accuracy. But it’s less clear how AI will work in the physician’s office or other clinical settings, the team said.

According to the team, previous attempts to use computer-assisted diagnosis shows that some screeners rely on the machine too much, which leads to repeating the machine’s errors, or under-rely on it and ignore accurate predictions.

The research team at Google AI believes that some of these pitfalls may be avoided if the computer can “explain” its predictions.

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Recent advances in AI promise to improve access to diabetic retinopathy screening and to improve its accuracy. But it’s less clear how AI will work in the physician’s office or other clinical settings, the team said. Pixabay

To test this theory, ten ophthalmologists (four general ophthalmologists, one trained outside the US, four retina specialists, and one retina specialist in training) were asked to read images with and without algorithm assistance.

Also Read: U.S. Government Human Rights Report Shows ‘Amber’ Warning Light Situation in Hong Kong

Without assistance, general ophthalmologists are significantly less accurate than the algorithm, while retina specialists are not significantly more accurate than the algorithm.

With assistance, general ophthalmologists match but do not exceed the model’s accuracy, while retina specialists start to exceed the model’s performance. (IANS)