Communication Strategies and Speech-to-Text Transcription

By Amanda Demas and Amanda Ortmann

This article is a part of the September/October 2021, Volume 33, Number 5, Audiology Today issue.

Speech-to-text transcription (STT) is the process of converting spoken words into text. STT does not refer to the captions themselves, but rather to the process of creating them. STT serves as an umbrella term that does not indicate how speech is transcribed, only that speech is being transcribed in some way. 

The transcription process can be achieved either by human efforts or by artificial intelligence (AI). AI is defined as “the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages” (Oxford Languages, 2021). 

STT is important for individuals who are d/Deaf or hard of hearing (U.S. Equal Employment Opportunity Commission, 2014). Additionally, STT is beneficial for the “normal” hearing population in environments with a poor signal-to-noise ratio (SNR), as well as in educational environments and for those who are second-language learners (Cucchiarini et al, 2000; Liao et al, 2020; Li, 2016). 

Individuals in any of these situations are considered learners because they are often expected to listen, take notes, integrate information, and ask questions. If proper content access is not provided for these individuals and situations, learning may be compromised. 

STT can be used in classrooms, meetings, conferences, movies, television shows, phone calls, and even small-group or one-on-one conversations. Regardless of the situation, STT has the ability to provide access to speech through real-time transcription.