Speech-to-Text Technology: Revolutionizing Communication and Accessibility

By Mehrnoush Mokhtarnejad

Introduction 

Speech-to-text technology (STT), also known as speech recognition, enables spoken words to be converted into digital text. STT has evolved significantly since its early development at AT&T Bell Laboratories in 1952. Over the decades, advancements in artificial intelligence and machine learning have propelled STT from basic voice recognition systems that required pauses between words to sophisticated programs capable of understanding continuous speech with high accuracy [1]. Today, speech-to-text is available through various applications, software programs, and devices. Mobile apps like Dragon Anywhere allow users to dictate text on their smartphones and tablets. Advances in artificial intelligence and machine learning have dramatically improved the accuracy of speech-to-text in recent years. While early systems required users to pause between each word, today's technology can handle natural, continuous speech. Some programs can achieve accuracy rates of 95% or higher and provide contextual suggestions. The technology has moved from requiring individual user adaptations to utilizing deep learning algorithms that offer 90–95% accuracy in prevalent languages. This evolution is evident in products from Dragon Systems and integrated software in devices like Apple's iPad, which have greatly enhanced user interaction by simplifying the process of creating digital text through speech [2] [3].

Applications in Diverse Environments

Speech-to-text can be beneficial as an assistive technology in different conditions. In educational settings, STT serves as a crucial assistive tool, particularly as students transition from primary to secondary education, where the demands for writing increase. Research indicates that STT can assist students with writing difficulties by enabling them to compose text through speech, thus bypassing the mechanical challenges of writing. This technology is particularly beneficial in accommodating students' varied abilities to adapt to new learning methods [2].

STT also supports diverse learning environments, aiding not only native speakers but also non-native speakers and students with disabilities. For instance, during lectures, students facing auditory challenges or network issues can rely on real-time text streams to follow discussions. Moreover, STT combined with computer-aided translation technologies in multilingual settings facilitates cross-cultural communication, enhancing understanding and engagement among international students [4].

Special Focus on Disabilities

STT technology holds transformative potential for individuals with developmental disabilities. For those with hearing impairments, advancements in STT applications like the "Deaf Chat" mobile app show promise in creating more inclusive communication environments. This app incorporates multiple-speaker classification technology to support conversations involving multiple participants, significantly improving over previous models [5].

Research involving students with traumatic brain injuries (TBI) has demonstrated that STT can significantly improve writing outcomes. By using speech-to-text as a writing accommodation, students are able to bypass the physical limitations of handwriting and spelling, focusing instead on the content and organization of their thoughts. Studies have shown that this technology not only increases the quantity of written output but also enhances the quality, providing students with the means to express more complex ideas and engage more fully in the educational process [6].

For individuals with physical impairments that make typing difficult, impossible, or painful, speech-to-text allows for hands-free computing and communication. This includes people with repetitive strain injuries, arthritis, and paralysis. Speech-to-text can help students with learning disabilities like dyslexia and dysgraphia complete writing assignments independently. By dictating instead of typing or handwriting, they can focus on composing their thoughts without struggling with the mechanics of writing [7]. Research shows speech recognition can increase writing output and quality for students with learning disabilities. People with visual impairments can use their voice to control devices and input information that would otherwise require seeing a screen or keyboard. For those with hearing loss, real-time speech-to-text transcription, such as closed captioning during live events, provides communication access [8].

Conclusion

Speech-to-text technology enhances functional communication across various domains and plays a pivotal role in educational and personal empowerment for individuals with developmental disabilities. By alleviating the mechanical burdens of writing, STT allows individuals to devote more cognitive resources to communication's creative and critical aspects. As technology continues to evolve, its integration into educational and social tools promises further advances in accessibility and user engagement, heralding a future where all individuals can communicate more freely and effectively [9].

In conclusion, speech-to-text technology has come a long way since the early days of speech recognition. It now enables hands-free, eyes-free computing across a range of devices and applications. While beneficial for all users, speech-to-text is a particularly impactful assistive technology for individuals with disabilities that make traditional input methods difficult. As this technology continues to improve in accuracy and availability, it has the potential to greatly increase access and independence for people with disabilities.

References

[1] Evmenova, A. S., & Regan, K. (2019). Supporting the writing process with technology for students with disabilities. Intervention in School and Clinic, 55(2), 78-85.

[2] Matre, M. E., & Cameron, D. L. (2024). A scoping review on the use of speech-to-text technology for adolescents with learning difficulties in secondary education. Disability and Rehabilitation: Assistive Technology, 19(3), 1103-1116.

[3] Nordström, T., Nilsson, S., Gustafson, S., & Svensson, I. (2018).  Assistive technology applications for students with reading difficulties: special education teachers’ experiences and perceptions. Disability and Rehabilitation: Assistive Technology.

[4] Shadiev, R., Wu, T. T., Sun, A., & Huang, Y. M. (2018). Applications of speech-to-text recognition and computer-aided translation for facilitating cross-cultural learning through a learning activity: issues and their solutions. Educational Technology Research and Development, 66, 191-214.

[5] Shezi, M., & Ade-Ibijola, A. (2020). Deaf chat: A speech-to-text communication aid for hearing deficiency. Advances in Science, Technology and Engineering Systems Journal, 5(5), 826-833.

[6] Noakes, M. A., Schmitt, A. J., McCallum, E., & Schutte, K. (2019). Speech-to-text assistive technology for the written expression of students with traumatic brain injuries: A single case experimental study. School Psychology, 34(6), 656.

[7] Caute, A., & Woolf, C. (2016). Using voice recognition software to improve communicative writing and social participation in an individual with severe acquired dysgraphia: An experimental single-case therapy study. Aphasiology, 30, 245–268. 

[8] Shadiev, R., Huang, Y. M., & Hwang, J. P. (2017a). Investigating the effectiveness of speech-to-text recognition application on learning performance, attention, and meditation. Educational Technology Research and Development. https://doi.org/10.1007/s11423-017-9516-3. 

[9] Khan, M. N. H., Arovi, M. A. H., Mahmud, H., Hasan, M. K., & Rubaiyeat, H. A. (2015, December). Speech based text correction tool for the visually impaired. In 2015 18th International Conference on Computer and Information Technology (ICCIT) (pp. 150-155). IEEE.