PERHAPS THE WORLD'S MOST ADVANCED
Cloud Transcriber is the next generation of Machine Transcription Engine where it transcribes the speech inside audio and video files and converts them into text.
The Cloud Transcriber platform leverages on Microsoft Research's Deep Neural Net (DNN) technology and speech recognition algorithms to provide you with the highly accurate speech-to-text conversion at a fraction of a professional transcription service prices.
Things that sets us apart
#1 DEEP NEURAL NET (DNN)
The technology behind our Machine Transcription is a powerful media processor that performs speech-to-text conversion on video or audio format. This media processor leverages Deep Neural Net (DNN)-based speech recognition technology from Microsoft Research and has consistently outperformed industry-standard speech transcription technology.
It is reassuring to know that you will be using to process your speech is the result of millions of dollars and thousands of hours of research. This is as good as it gets!
#2 HIGHLY SCALABLE
This simply means that we can handle large volume of jobs at the same time because we are not dependent on a single server to run jobs sequentially. As we are harnessing the scalability of the Cloud, we are able to run 1,000 jobs concurrently at same time! Which also means that our turn-around time is not dependent on our hardware.
#3 AUTO-GENERATION OF KEYWORDS
Our media processor auto-generates a set of algorithmically-determined keywords form the input audio and video along with their confidence level.
#4 You can IMPROVE THE ACCURACY
Really! You can! Unlike other machine transcription engines, you can give us a set of keywords that is associated with your audio/video file to be transcribed. For example, scientific and medical terms, a person's name or even a technical part name, etc. This is what we do with these terms:
- Our Engine will rank these words/terms into a higher order and use them first when a similar sounding word appears.
- We use these words as a search term to search the web for related documents and use these documents to expand its our Transcription Engine's vocabulary with the final aim to improve search results.