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How Taking Music Lessons Can Improve Your Language Skills

A recent MIT study has revealed that taking piano lessons as a youngster can, in fact, help children to better distinguish between different pitches. Being able to distinguish sounds in such as way translates into an improvement in being able to better discriminate between spoken words.

Daniel Okafor
Daniel OkaforSenior AI Reporter
3 min read
How Taking Music Lessons Can Improve Your Language Skills

A recent MIT study has revealed that taking piano lessons as a youngster can, in fact, help children to better distinguish between different pitches. Being able to distinguish sounds in such as way translates into an improvement in being able to better discriminate between spoken words.

“The children didn’t differ in the broader cognitive measures, but they did show some improvements in word discrimination, particularly for consonants. The piano group showed the best improvement there,” confirms Robert Desimone, senior author of the paper and director of MIT’s McGovern Institute for Brain Research and the senior author of the paper.

Results from the study were published in the journal Proceedings of the National Academy of Sciences just last month. The findings suggest that having music tuition is quite possibly more beneficial for a child than having extra reading lessons. This supports previous research carried out that has shown how musicians tend to perform better than nonmusicians when it comes to tasks such as rapid auditory processing, separating speech from background noise, and reading comprehension.

But the MIT study added a little more to the equation as they wanted a more strict study that involved randomly picking children to receive music lessons and measuring how well they performed. This study was carried out in a school in Beijing and involved 74 children who were divided into three groups: those that received extra reading tuition 45-minutes per week; those who received 45-minute piano lessons; and those that had neither. All children were aged between 4 and 5 years old, speaking Mandarin as their native language.

After just six months, those children who received piano lessons had a much better ability to discriminate words based on differences in vowels, consonant, or tone than those who had extra reading lessons. Both performed better than those children that had neither. It was also found that those in the piano group had a better response to tones of a different pitch than the others, suggesting that a greater sensitivity to pitch is what helped these same children discriminate between different words.

When it came to the children’s IQ, working memory, and attention the researchers found no real differences between the three groups. This suggests that while the piano lessons did improve the children’s ability to distinguish between different tones and words, there was no real effect on their overall cognitive function.

“This study answers the question in the affirmative, with an elegant design that directly compares the effect of music and language instruction on children,” says Aniruddh Patel, a professor of psychology at Tufts University. “The work specifically relates behavioral improvements in speech perception to the neural impact of musical training, which has both theoretical and real-world significance.”

Desimone is hopeful the findings will be used to help convince schools to promote music lessons, not abolish them. “There are positive benefits to piano education in young kids, and it looks like for recognizing differences between sounds including speech sounds, it’s better than extra reading,” he says. The next move for Desimone is to take a deeper look into the neurological changes brought about by music by performing EEG tests before and after some intense music tuition to see how the brain activity alters.

Image; DepositPhotos

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Daniel Okafor

Daniel Okafor

Senior AI Reporter

Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.

All stories by Daniel Okafor (316)