Use the following bash script to convert them all to txt files. The transcription files stored in the Documents directory will be in rtf format, and need to be converted to plain text.
#WATSON SPEECH TO TEXT ZIP#
The downloaded files will be contained in zip files.Ĭreate both an Audio and Documents subdirectory inside the data directory and then extract the downloaded zip files into their respective locations.
#WATSON SPEECH TO TEXT DOWNLOAD#
Go to the ezDI web site and download both the medical dictation audio files and the transcribed text files. Save off the apikey and url values as they will be needed in future steps. If no credentials exist, select the New Credential button to create a new set of credentials. Configure credentialsįrom your Watson Speech to Text service instance, select the Service Credentials tab. Note: In order to perform customization, you will need to select the Standard paid plan.
Enhance the model with continuous user feedback.Train a custom speech-to-text model with a data set.Work with the Watson Speech to Text service through API calls.Prepare audio data and transcription text for training a speech-to-text model.
#WATSON SPEECH TO TEXT CODE#
When the reader has completed this code pattern, they will understand how to:
The data is provided by ezDI and includes 16 hours of medical dictation in both audio and text files. In this example, we will use a medical speech data set to illustrate the process. To improve the accuracy of the speech-to-text service, you can leverage transfer learning by training the existing AI model with new data from your domain. However, like other Cloud speech services, it was trained with general conversational speech for general use therefore it may not perform well in specialized domains such as medicine, law, sports, etc. The Watson Speech to Text service is among the best in the industry.
In this code pattern, we will create a custom speech to text model. Create a custom Watson Speech to Text model using specialized domain data