Talk Code-y To Me: An analysis of speech to text systems for consideration of use in writing software

Abstract

This study proposes to create an application to allow ease of Speech to Text (STT) conversion specifically for programmers to make programming more accessible to those with disabilities. Recently there is being a movement of pairing STT with other disciplines now that STT is readily available and reliable. The main questions are how well Apple’s STT performs, is Apple’s STT ready to be integrated with coding, how do programmers interpret and speak code aloud, and how well does a formatting application created for this study to format transcriptions into executable code perform. The study concludes that Apple’s STT transcribes text at an average success rate of 50.1% and in correctly transcribing and interpreting words at an average success rate of 13.12%, whether it is ready to be used in coding is up to the reader, programmers interpret and speak code in wide range of ways, and the application had a success rate of 0% but the data collected will help it to improve in the future.

Description

Keywords

Speech to text, speech to text recognition, apple speech to text

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