When most people think about speech recognition, they think about personal assistant applications like Siri or Alexa. But as speech technology becomes cheaper and faster, we're seeing more and more use cases in domains and industries where speech-to-text tools haven't been used much in the past. In this post, we're going to discuss 7 of the most common use cases of speech recognition for learning and education, as well as who can benefit most from this technology. But to start, let's clarify what speech recognition in learning is.
What is Speech Recognition for Learning?
In short, any use of speech-to-text for education is an example of speech recognition in learning. As will see below, this can refer to different things, but at their core, they all involve turning the spoken interactions that happen in the classroom into transcribed text. But beyond that, there are a lot of different ways that these transcriptions can be used.
7 Top Use Cases for Speech Technology in Education
Let's take a look at the top 7 use cases for speech-to-text in education, including how they can benefit students and teachers alike.
1. Classroom Transcripts
Speech recognition can be used to create transcripts of lectures and classroom discussions. We've previously talked about the benefits of classroom captions, and even built a project to showcase the technology, but in short, transcripts are especially useful for students who are hard of hearing or have difficulty taking notes, as well as non-native speakers who might not understand every word of a lecture. Transcripts let these students refer to lecture content after the fact to help them master the material.
2. Study Aids
Creating materials for study and test prep is another domain where speech recognition can help. For example, there are apps that can create flashcards based on a student's lecture notes-or, even better, a transcript of a lecture. And even if you don't make flashcards automatically, having the transcription of what was said can make it much easier to prep study materials manually, as well as search to find specific terms or things that weren't understood during the lecture.
3. Video Subtitles & Captioning
Speech recognition can also be used to create subtitles for educational videos. This is helpful for students who are deaf or hard of hearing. It can also be helpful for students who speak English as a second language. These subtitles can also be used as closed captions on live videos. With hybrid class environments, this can be a boon for anyone who is attending remotely, as they might not be able to hear what was said in the class well. For example, Habitat Learn offers a service like this, providing real-time transcripts of classes. If you want to learn more about the work that Habitat Learn is doing, check out our upcoming webinar with them!
4. Research Projects
Some research projects require students to transcribe interviews or speeches. Speech recognition can be used to make this task easier. This can have impacts beyond the classroom as well, helping researchers to better understand data they glean from interviews, by giving them access to a searchable database of all of their interviews, without having to spend time manually transcribing them.
5. Pronunciation Assessments
Speech recognition can be used to help students learn languages. For example, there are applications that allow students to practice their pronunciation by speaking into the app. Automatic speech recognition can be used to assess a student's pronunciation skills. This is valuable for language learners who need to practice their speaking skills, or want to check how well they're pronouncing certain words or phrases.
6. Assistive Technologies
Automatic speech recognition can also be used to create accessible education materials for students with disabilities. For example, students who are blind or have low vision can use text-to-speech applications to listen to textbooks and other educational materials. Students who are deaf or hard of hearing can use automatic speech recognition to create subtitles for education videos. Speech recognition can be used to help students with dyslexia write essays by allowing dictation and readback of the content.
7. Class Prep
Our final benefit isn't for students, but for teachers. Teachers often have to teach the same material over and over, whether to different classes on the same day or week, or year after year. By referring to their transcripts after class, instructors can make updates to their lesson plans and materials for future classes, review and better understand student questions, and remind themselves of content they promised to follow up on. And, with features like diarization and speaker ID, these transcripts can even help with assigning participation and attendance after class.
Who Can Benefit from Voice Technology in Education?
As we've seen, almost any student can benefit from having the ability to revisit class material after the fact to study. But some students see particular benefits from this technology. This applies to anyone who might have trouble hearing or understanding what was said in class, whether because they are hard of hearing, not a native speaker of the language being used in the classroom, or have a learning disability that makes understanding lectures difficult. Additionally, in the current COVID environment, these tools can help keep all students on track. If students have to miss class due to illness, or attend remotely due to quarantining, tools like captioning and class transcripts can help make sure they stay on top of what's happening in the classroom. These technologies, used correctly, can truly help to put everyone in the classroom on the same footing when it comes to understanding and engaging with the lecture material.
In conclusion, automatic speech recognition solutions have a wide range of applications in education. These technologies can be used to create transcripts, assess pronunciation skills, and create accessible education materials for students with disabilities. If you're looking to get started with a speech-to-text solution, feel free to contact us and we'll be happy to discuss your use case and help you get started. Or, you can sign up for Console for free and get $150 in credits to give Deepgram a try.
If you have any feedback about this post, or anything else around Deepgram, we'd love to hear from you. Please let us know in our GitHub discussions.
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