Wednesday June 19, 2019

Language Lessons For Your Baby May Start in Womb

The study showed that foetuses can hear things, including speech in the womb

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The findings if a new study by MIT researchers could offer a possible way to reduce the risk of autism. Pixabay
  • A baby can distinguish the difference between sounds used in various languages even a month before being born
  • The study showed that foetuses can hear things, including speech in the womb
  • The team examined 24 women, averaging roughly eight months pregnant

New York, July 18, 2017: Love to speak to your unborn baby? Well he or she can typically distinguish the difference between sounds used in various languages even a month before being born, an interesting study has shown.

The study showed that foetuses can hear things, including speech, in the womb, although the voice is muffled.

In the study, the foetal heart rates changed when they heard the unfamiliar, rhythmically distinct language (Japanese) after having heard a passage of English speech, while their heart rates did not change when they were presented with a second passage of English instead of a passage in Japanese.

“The results suggest that language development may indeed start in utero. Foetuses are tuning their ears to the language they are going to acquire even before they are born, based on the speech signals available to them in utero,” said lead author Utako Minai, associate professor from the University of Kansas.

Also Read: Pregnancy seems Safe for Breast Cancer Survivors: Study

“Pre-natal sensitivity to the rhythmic properties of language may provide children with one of the very first building blocks in acquiring language,” Minai added.

For the study, published in the journal NeuroReport, the team examined 24 women, averaging roughly eight months pregnant.

Minai had a bilingual speaker make two recordings, one each in English and Japanese — argued to be rhythmically distinctive language, to be played in succession to the foetus.

“The intrauterine environment is a noisy place. The foetus is exposed to maternal gut sounds, her heartbeats and voice, as well as external sounds.

“Without exposure to sound, the auditory cortex wouldn’t get enough stimulation to develop properly. This study gives evidence that some of that development is linked to language,” explained Kathleen Gustafson, a research associate professor at the varsity. (IANS)

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Researchers Develop New App to Detect Twitter Bots in Any Language

According to the researchers, the app is light, making it possible to classify vast amounts of data quickly and relatively efficiently

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The logo for Twitter is displayed above a trading post on the floor of the New York Stock Exchange. vOA

Researchers have developed a new application that uses Machine Learning (ML) to detect Twitter bots in any language.

The study presented at the fourth conference of Digital Humanities in the Nordic Countries shows that the application is able to detect auto-generated tweets independent of the language used.

“This enhances the quality of data and paints a more accurate picture of the reality,” said Mikko Laitinen, Professor at the University of Eastern Finland.

In recent years, big data from various social media applications have turned the web into a user-generated repository of information in the ever-increasing number of areas, said the researchers.

Twitter has become a popular source of data for investigations of a number of phenomena Because of the relatively easy access to tweets and their meta-data.

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FILE – A man reads tweets on his phone in front of a displayed Twitter logo. VOA

Twitter Bots are non-personal and automated accounts that post content to online social networks.

It has been estimated that around 5 to 10 per cent of all users are bots and these accounts generate about 20-25 per cent of all tweets posted.

For the study, the researchers analysed 15,000 tweets in Finnish, Swedish and English. Finnish and Swedish were mainly used for training, whereas tweets in English were used to evaluate the language independence of the application.

Also Read- Google Announces an Investment of $600 mn to Expand US Data Centre

According to the researchers, the app is light, making it possible to classify vast amounts of data quickly and relatively efficiently.

“Bots are relatively harmless, whereas trolls do harm as they spread fake news and come up with made-up stories. This is why there’s a need for increasingly advanced tools for social media monitoring”, said Laitinen. (IANS)