What Role Does Speech Recognition Technology Play in Advanced Learning?

If you have a smartphone, chances are you’re engaging with speech recognition technology daily. According to ComCast, over half of smartphone users are tapping into this ever-developing technology.

From speech-to-text memos to Siri and Alexa, this powerful AI tool has become a regular fixture in our daily lives. It allows for more human interaction between user and machine, giving people the freedom to talk naturally and get nuanced results. 

All of these technologies can translate spoken language into digitized text, and analyze speech for recognizable commands. Some of these products function like contact center speech analytics software, detecting key phrases which trigger desired responses.

Advanced AI solutions offer a new range of applications: devices trained to respond to a specific voice, and learning a particular user’s phrasing and mannerisms over time. In time this will allow for truly natural interfacing between humans and machines.

However, the ramifications for learning and education are still being explored. Speech-to-text and voice recognition software has been available to students with physical disabilities and special learning needs for many years, but inconsistent implementation in schools and colleges has given us an incomplete sense of the technology’s efficacy. 

Educators are hoping that the tide is turning with both Microsoft and Apple building speech recognition into their recent updates. This not only allows students with disabilities a more normalized and discrete way to access learning resources, but it has also piqued the interest of students in mainstream advanced education.

Read on to discover how speech recognition technology is changing the game and improving accessibility for students in advanced learning.

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Leveling the Playing Field

One of the most compelling aspects of speech recognition technology is its potential to make learning at all levels accessible for those who have previously experienced difficulty engaging with typed or written text.

For example, those with dyslexia or dysgraphia frequently experience frustration with note-taking or typing up written work. In primary and secondary education, these students are liable to fall by the wayside and be dismissed as academically ungifted as a result of their struggles with writing.

With voice-to-text apps on their side, however, these students can quickly and naturally commit their thoughts to writing, circumnavigating the processes that cause them difficulty. Likewise, students with visual impairments can dictate their thoughts directly to their devices, saving time and increasing confidence.

Thanks to powerful machine learning, some speech recognition tools can be trained to understand and translate the nuances of specific voices over time. Such tools are invaluable to speech language pathology, where students may be unable to access conventional voice recognition apps due to difficulties with speaking or annunciating.

Those with motor skill disorders, long or short-term physical disabilities, or even repetitive strain injuries such as carpal tunnel syndrome will also find that speech recognition increases writing production and enhances independent learning. 

Everyday Application

The benefits of speech recognition and speech-to-text can benefit learners both in and out of the classroom. They make phones, computers, and tablets accessible to those with impairments that would otherwise make such devices off-limits. This allows learners to take responsibility for their own studies holistically.

For example, most smartphones now feature a voice-activated assistant, such as Apple’s Siri. These can act much like a business phone dialer, helping users to make calls, add people to their contacts, set alerts or calendar events, and take notes on conversations – all without needing to touch a button.

Speech-to-text developments have already seen successful application in the customer service industry, especially call centers for small businesses. Voice recognition allows customers to interface with bots and access the information they need quickly and easily.

Educational establishments can take cues from the business world by creating directories or resource libraries with similar voice-driven access points. This will allow users of all abilities to explore information relevant to their courses by speaking simple commands to a voice-activated system.

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Classroom Uses

These benefits only multiply when brought into a classroom setting, offering improved access to courses both in college and as part of rapid elearning in the workplace. Voice recognition technology removes the physical barriers to writing and computing, making previously inaccessible courses friendly to all learners.

Educators suggest that over time, speech-to-text tools can even help students gain a better understanding of writing and spelling. By watching the words they dictate appear on the screen, learners can develop a natural appreciation of the relationship between phonemes and spelling patterns. This can help advanced learners increase their literacy even as they engage with more complex subjects.

This technology can also boost the wider skill of writing, encouraging deeper engagement from students with learning disabilities. Adult writers with learning disabilities typically elect to skip out words or sentiments if they’re unsure of the correct spelling of grammar, resulting in short, surface-level pieces of writing which do not reflect the student’s abilities or thought processes.

By leaving spelling correction to voice-to-text technology and a word processor, learners can turn their minds to the more rewarding task of expressing their thoughts, without worrying about technical aspects of putting ideas on paper. Using verbal input, they will find themselves able to use more complex vocabulary and sentence structure.

Particularly given the importance of STEM education for career growth, this encouragement to engage with complex subjects can have a lifelong effect on learners.

This reprioritization has been shown to decrease anxiety in learners, allowing them to write without worrying about spelling errors or editing. While advanced learners often fear judgment of their writing, speech recognition technology removes the visual and technical aspects of writing that they’re so embarrassed by, making classroom learning a calmer, more supportive experience.

All these aspects come together to create more confident and independent learners, who can engage with lessons on their own terms without asking for help or involving a student aide. In fact, one organization found that students’ grades improved by 17% when using their speech recognition software.

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How to Boost Student Success With Speech Technology

Speech recognition technology can lead to a whole range of positive outcomes for blended learning, but it needs to be tailored to the individual student. If you’re considering introducing voice-to-text tech into a learning journey, take time to explore the different options available, and choose one which works best for your needs and lifestyle.

Invest in a computer with a high-quality microphone and sound card to decrease the likelihood of mistranscription. Many speech recognition software developers have their own recommendations for microphones that integrate well with their programs.

Whether you’re looking into speech technology to assist your own learning or helping a student or colleague, consider using voice-to-text tech in conjunction with programs designed to help boost adult literacy. Software that includes read-back or text-to-speech functions can help improve reading speed and comprehension over time.

Challenges to Implementation

Speech recognition technology has gone from strength to strength in recent years and is rapidly becoming accepted as a part of everyday life. However, there are still a few unique challenges when it comes to incorporating it into advanced learning.

It can take a little time to get used to using the technology, particularly if training software to recognize your specific voice and speech patterns. In this interim period, mistranscriptions will be more frequent, and frustration could lead learners to drop the tool before the benefits become tangible.

While recent developments have led to greater app stickiness for speech technology applications, those who stick with it may find that speaking to write feels quite different from conversational dialogue. It could take time to learn to speak slowly and clearly enough to create quality written work, especially when brainstorming or note-taking.

The other significant barrier to speech recognition technology is the cost of the required equipment. While an occasional speech-to-text user may be fine with using their phone to take notes, learners with specific assistive technology will require ample hard drive space to host the required single server file.

Thankfully cloud servers can come to the rescue here, allowing learners to access the same personalized memory banks from their computers at home, and from loaned devices at school, college, or in the workplace. 

The greatest challenge is still improving tech accessibility in areas without specific funding for learning disabilities. In state-funded learning establishments, obtaining funding is a complicated process involving multiple assessments of students’ learning needs before a grant can be considered. Advanced learners often have to pay their own way with assistive technologies.

Fortunately, the mainstreaming of voice technologies is making it easier than ever to find an affordable combination of software and hardware, with voice-to-text programs and voice-operated assistants now available as standard on many computers and tablets.

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Conclusion

Whether you are still asking “what is speech analytics?” or you’ve already experimented with voice-to-speech technologies, you’re likely to come across speech recognition more and more over the coming years. 

As different industries adopt voice recognition technology into their workflow processes, users of assistive technologies find themselves less stigmatized and more confident. In some cases, apps designed for learners with disabilities have become streamlined into mainstream systems, becoming relied on by lesser-abled and neurotypical learners alike.

The technology is continuing to advance and find new applications, from learning tools to automated operators. Is speech recognition technology the future of interfacing with machines? Some industry leaders certainly think so – but more importantly, it may help humans of different abilities interface with one another.