Improving the enunciation of speech-to-text technology in medical settings

Speech-to-text programs are becoming more popular for everyday tasks like hands-free dictation, helping people who are visually impaired, and transcribing speech for those who are hard of hearing. These tools have many uses, and researcher Bożena Kostek from Gdańsk University of Technology is exploring how STT can be better used in the medical field. By studying how clear speech affects STT accuracy, she hopes to improve its usefulness for health care professionals.

“Automating note-taking for patient data is crucial for doctors and radiologists, as it gives the doctors more face-to-face time with patients and allows for better data collection,” Kostek says.

Kostek also explains the challenges they face in this work.

“STT models often struggle with medical terms, especially in Polish, since many have been trained mainly on English. Also, most resources focus on simple language, not specialized medical vocabulary. Noisy hospital environments make it even harder, as health care providers may not speak clearly due to stress or distractions.”

To tackle these issues, a detailed audio dataset was created with Polish medical terms spoken by doctors and specialists in areas like cardiology and pulmonology. This dataset was analyzed using an Automatic Speech Recognition model, technology that converts speech into text, for transcription. Several metrics, such as Word Error Rate and Character Error Rate, were used to evaluate the quality of the speech recognition. This analysis helps understand how speech clarity and style affect the accuracy of STT.

Kostek presented this as part of the virtual 187th Meeting of the Acoustical Society of America.

“Medical jargon can be tricky, especially with abbreviations that differ across specialties. This is an even more difficult task when we refer to realistic hospital situations in which the room is not acoustically prepared,” Kostek said.

Currently, the focus is on Polish, but there are plans to expand the research to other languages, like Czech. Collaborations are being established with the University Hospital in Brno to develop medical term resources, aiming to enhance the use of STT technology in health care.

“Even though artificial intelligence is helpful in many situations, many problems should be investigated analytically rather than holistically, focusing on breaking a whole picture into individual parts.”