I am a software developer, and I develop medical applications that transcribe appointments between doctors and patients. Afterward, the transcription is processed to create a report based on specific medical structures. I used AWS Transcribe for this transcription service, which I utilize daily. This was one of my applications. Another application is related to an educational platform similar to Udemy or Coursera, where video content is uploaded. My client wanted a platform where the video and text description are uploaded, and actions are automatically written by the system. I implemented AWS Transcribe to get the transcription and processed it with artificial intelligence models, such as OpenAI, to obtain the processed text for each video.
I use Amazon Transcribe primarily for Skype and Webex sessions for Cloudera. I have an application that I use mainly for conducting classes at the start of a Sprint. I always record these classes, and sometimes students request transcripts of the lectures. I use Transcribe to convert my speech to text and deliver it as both audio and video to my students. Additionally, I attend recorded meetings and use Transcribe to convert them to text and summarize the highlights. This is especially helpful when I miss a meeting.
Lately, I've been using AWS Transcribe for transcriptions. I do have some videos that are a client requirement that convert meetings and videos into audio so that audio can be used as an input factor of the transcript can get transcribed.
Speech-To-Text Services are essential for converting spoken language into written text efficiently. These services benefit a range of applications, from transcribing meetings to content creation, facilitating easier information access and management.Speech-To-Text Services use advanced machine learning models to accurately transcribe spoken words into text. They are crucial in fields requiring documentation and accessibility, such as education, media, and customer service. Service providers...
I am a software developer, and I develop medical applications that transcribe appointments between doctors and patients. Afterward, the transcription is processed to create a report based on specific medical structures. I used AWS Transcribe for this transcription service, which I utilize daily. This was one of my applications. Another application is related to an educational platform similar to Udemy or Coursera, where video content is uploaded. My client wanted a platform where the video and text description are uploaded, and actions are automatically written by the system. I implemented AWS Transcribe to get the transcription and processed it with artificial intelligence models, such as OpenAI, to obtain the processed text for each video.
I use Amazon Transcribe primarily for Skype and Webex sessions for Cloudera. I have an application that I use mainly for conducting classes at the start of a Sprint. I always record these classes, and sometimes students request transcripts of the lectures. I use Transcribe to convert my speech to text and deliver it as both audio and video to my students. Additionally, I attend recorded meetings and use Transcribe to convert them to text and summarize the highlights. This is especially helpful when I miss a meeting.
I am looking at different solutions for accessibility.
Lately, I've been using AWS Transcribe for transcriptions. I do have some videos that are a client requirement that convert meetings and videos into audio so that audio can be used as an input factor of the transcript can get transcribed.