Speech recognition (also known as automatic speech recognition or computer speech recognition) converts spoken words to machine-readable input (for example, to key presses, using the binary code for a string of character codes). Another limitation has been the extensive amount of time required by the user and/or system provider to train the software. The nature of narrative dictation is highly interpretive and often requires judgment that may be provided by a real human but not yet by an automated system. The biggest limitation to speech recognition automating transcription, however, is seen as the software. Additionally, to be used effectively, it required changes to the ways physicians worked and documented clinical encounters, which many if not all were reluctant to do.
It was also the case that SR at that time was often technically deficient. According to industry experts, at its inception, speech recognition (SR) was sold as a way to completely eliminate transcription rather than make the transcription process more efficient, hence it was not accepted. “One of the most notable domains for the commercial application of speech recognition in the United States has been health care and in particular the work of the medical transcriptionist. One of the most sought after inclusive technology products for students is actually a technology that was primarily designed for other purposes.
Creating text using voice in Speech Recognition Programsĭownload this document as an MS Word.