Tags:
create new tag
view all tags

Voice Recognition Software Is Proving Effective For Children In The Classroom

During the Covid-19 pandemic, as the plant locked down, every classroom closed! But children need to study and the tech sector has really stepped up in enabling learners to join in class from home.

It was big issue to solve, and there are many videos meeting software like Zoom, Meet, Hangouts and many others providing video calling services.

Another big problem here for children, when they go to class, they get help from teachers. But joining class from home, they donít get help from teachers properly. How you can fix this problem? Donít worry, as cutting-edge voice recognition software can now help children to get proper help in learning language-based outcomes with ease.

Popular voice assistants like Azure, Alexa, Soapbox Labs, Siri and Google use speech recognition software to answer your questions, but children's language is complex and unpredictable.

Sentences are often over-enunciated, certain syllables are elongated, each word is punctuated as they are thought aloud, and other terms are skipped entirely. Children spend up to 5 hours every day in front of devices. Thus, they must be understood.

Before the pandemic, children made up more than 40% of new internet users. According to current estimates, children's screen usage has increased by 60% or more, with children aged 12 and underspending up to five hours per day on screens.

In this context, digital assistants powering voice AI in children's education offer the prospect of a more frictionless relationship with technology. However, while children like asking Alexa or Siri to beatbox, tell jokes, or make animal sounds, parents and teachers are aware that these systems struggle to understand their children when they depart from typical requests.

Kid-Centric Voice AI is Evolving

The currently problem faced by the major voice tech companies is that the speech recognition software that powers popular voice assistants like Siri, and Google was never built for use with children whose voices, vocabulary, and behavior are significantly more sophisticated than adults'.

Not only are children's voices squeakier, but their vocal tracts are thinner and shorter, their vocal folds are more minor, and their larynx is not fully grown. This generates speech patterns substantially different from those of an older child or an adult and it takes specialist, child-centric voice AI like Soapbox to accurately detect and interpret this speech data.

Just changing the pitch of adult voices to train speech recognition fails to replicate the richness of information needed to understand a child's speech. Language structures and patterns in children differ widely. They make leaps in syntax, pronunciation, and grammar that speech recognition systems' natural language processing component must account for. Interspeaker variability among children at various developmental stages adds to the complexity, which cannot be accounted for with adult speech.

The speaking behavior of children is not only more changeable than that of adults but also wildly chaotic. Their speech patterns are not constrained by the general cadences seen in systems designed for adults. As adults, we've figured out how to interact with these technologies in the most effective way possible.

In contrast to other consumer situations, accuracy has significant ramifications for children. A system that tells a child they're wrong when they're right hurts their confidence; one that tells them they're right when they're wrong threatens socioemotional harm. These false negatives or positives contribute to frustrating encounters in entertainment settings, such as apps, gaming, robotics, and intelligent toys. Errors, misunderstandings, and prefabricated school replies can have much more severe educational and equity consequences.

Speech recognition software also has the potential to improve classroom fairness. Human reading evaluation is, after all, very subjective, with assessor bias causing differences of up to 18% in recent research.

Today's child-centered, high-accuracy speech recognition overcomes human prejudice by ensuring that every child's voice is comprehended regardless of accent or dialect Ė and this is most certainly a good thing for the future of our childrenís educations.

-- Abdul Alim - 2022-05-24

Comments


Topic revision: r1 - 2022-05-24 - AbdulAlim
 
This site is powered by the TWiki collaboration platform Powered by PerlCopyright © 2008-2023 by the contributing authors. All material on this collaboration platform is the property of the contributing authors.
Ideas, requests, problems regarding TWiki? Send feedback