Speech to Text Prescription Writer

Inspiration

Upon reflecting on the pandemic it was evident that hospitals had an overwhelming amount of patients with a lack of staff. This left doctors overwhelmed and patients with sub-par treatment. At this time hospitals should have begun automating or speeding up non-paitent related tasks such as writing prescriptions. It is becoming increasingly difficult for doctors to handwrite prescriptions and keep track of all of their patients as the patient population grows. The proposed method will allow doctors to speak their prescriptions vocally rather than typing or writing them manually, saving time for both doctors and patients and reducing human error to a greater extent

How we built it

We built it using a variety of python packages it starts with speech recognition and py audio working hand in hand with Tkinter constantly providing pop-up windows and pypdf creating a clean PDF prescription.

Challenges we ran into

During this Hackathon, the most notable challenge the team faced was in regards to the functionality behind the Speech Recognition. During our testing phases, our original framework functioned accordingly, but once integrated into the project is where we saw many errors. However, after achieving a deep understanding of the module documentation and configuring of certain hardware, the group was able to overcome this issue and create an amazing project.

Accomplishments that we're proud of

Multiple accomplishments that we're proud of include being able to implement a half efficient voice recognition module, being able to program roughly 260 lines in only a small amount of time, lastly, making a program successfully using modules and packages that we never used before.

What we learned

Our team discovered a lot of things as a result of the procedure. The most important thing we learned was that when it comes to working on an application, time management and organization are subtle but critical variables in the completion of a Hackathon that is especially run during a short time span. In addition, our team explored a variety of modules that we had never come across, which further expanded our knowledge as we read through the documentation and applied it to our project.

What's next for Speech to Text Prescription Writer

Next is to increase and improve the efficiency of the program to decrease chances of error to under 1%, also to create other programs that use speech recognition in the medical field to make doctors jobs all the easier