AWS Transcribe – Use cases

At the re:invent2017 AWS presented AWS Transcribe (read more about new AWS announcements here: AWS Comprehend, Translate and Transcribe).

Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech to text capability to their applications. Using the Amazon Transcribe API, you can analyze audio files stored in Amazon S3 and have the service return a text file of the transcribed speech.

Use cases

Amazon Transcribe can be used for lots of common applications, for example:

  • transcription of customer service calls
  • generation of subtitles on audio and video content
  • conversion of audio file (for example podcast) to text
  • search for key words or not safe for work words within an audio file

The service is still in preview, watch the launch video here: AWS re:Invent 2017: Introducing Amazon Transcribe
You can read more about it here: Amazon Transcribe – Accurate Speech To Text At Scale.

Here how to use AWS Transcribe with the Python SDK. Please notice that the service is still in preview.
Here you can find the documentation: Boto3 AWS Transcribe.

Initialize the client:

Run the transcribe job:

Check the job status and print the result:

Here how the output looks like:

Soon I am going to use AWS transcribe to build a speech to text recognition system that will process customer care recordings in order to:

  • convert speech to text (using AWS Transcribe)
  • extract entites, sentiment and key phrases from the text (using AWS Comprehned)
  • index the result to Elasticsearch for fast search

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