Catastrophic Mishaps in Medical Audio: Audiologists Witness the Worst-Case Scenarios
In the realm of voice-transcription audio software, precision is not always guaranteed, as evident in interview notes for a recent Cosmos article, where the term "hearables" was repeatedly rendered as "hair balls." While this can often be amusing, mistakes are not so harmless in medical transcription, where errors could have catastrophic consequences.
Theoretically, voice transcription can streamline medical procedures, according to Kelly Scott, a primary-care physician in Portland, Oregon. However, the accuracy of the software hinges on correctly interpreting the user's words. One Issue with medical audio, asserts Bożena Kostek, a researcher from Gdańsk University of Technology, Poland, speaking at the online meeting of the American Society of Acoustics, lies in the software's reliance on English speakers during its training.
Beyond language bias, specialized medical terms pose further problems. For instance, an acronym that signifies one thing to a cardiologist could have a different meaning entirely for an oncologist. Another concern is that dictations are often made under noisy conditions, such as hospital rooms, where people converse simultaneously, and there's an abundance of beeps. Doctors attempting to express their notes in such circumstances may raise their voices, leading to Lombard speech, a phenomenon that distorts vowel duration, timbre, and other aspects, confounding audio-transcription programs.
To overcome these obstacles, Kostek suggests focusing on clear enunciation and avoiding ambiguous acronyms. However, overpronouncing words might be too much for the machine learning model to handle.
In an additional exploration, it has been found that human detectors of deepfake audio can be inconsistent, proving the challenges of relying solely on technology for accuracy in the medical field.
Adapted from an original article by Cosmos titled "Medical audio can go catastrophically wrong audiologists hear"
In the medical field, where even minor errors could have significant consequences, voice transcription technology's accuracy is crucial. However, the reliance on English speakers during its training and the interpretation of complex medical terms, such as acronyms with different meanings to specialists, pose challenges.
