In this step-by-step tutorial, you will learn how to use Amazon Transcribe to create a text transcript of a recorded audio file using the AWS Management Console. 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 Simple Storage Service (S3) and have the service return a text file of the transcribed speech.

As a developer, creating transcriptions of customer service calls or generating subtitles on audio and video content are common challenges requiring speech-to-text capabilities. This challenge could be solved by building your own machine learning models from scratch. However, this option is time-intensive, expensive, and requires machine learning expertise. Instead of taking the difficult route, you can use Amazon Transcribe, a pre-trained and fully-managed service, which provides fast and high-quality transcriptions.

In this tutorial you will download a sample audio file then upload it to a S3 bucket that you will create. Then you will use Amazon Transcribe to create a transcript from the sample audio clip using the AWS Management Console.

This tutorial is a demo of the functionality that is available when using the AWS CLI or the Transcribe API. For production or proof of concept implementations, we recommend using these programmatic interfaces rather than the Amazon Transcribe Console.

a.  When you click here, you will download the sample audio file to transcribe later in the tutorial. The file name is transcribe-sample.mp3.

b.  When you click here, the AWS Management Console will open in a new browser window, so you can keep this step-by-step guide open. When the screen loads, enter your user name and password to get started. Using the Region drop down, select a Region that has Amazon Transcribe.

At the time of writing, Amazon Transcribe is available in US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Sydney), Canada (Central), and EU (Ireland) regions.

c. Type S3 in the search bar and select S3 to open the console.

d.  In the S3 dashboard choose Create bucket.

If this is the first time you have created a bucket, you will see a screen that looks like the image pictured here.

If you have already created S3 buckets, your S3 dashboard will list all the buckets you have created.

e.  Enter a unique bucket name. Bucket names must be unique across all existing bucket names in Amazon S3. There are a number of other restrictions on S3 bucket names as well. Then select a Region to create your bucket in.

Select Next.

f.  You have many useful options for your S3 bucket including Versioning, Server Access Logging, Tags, Object-level Logging and Default Encryption. We won't enable these features for this tutorial.

Select Next.

g.  In this step you have the ability to adjust permission settings for your S3 bucket during the S3 bucket creation process.

Leave the default values and select Next.

h.  Review your configuration settings and select Create bucket.

i.  You will see your new bucket in the S3 console. Click on your bucket’s name to navigate to the bucket. Your bucket name will not be the same as pictured in the screenshot to the right.

j. You are in your bucket’s home page.

Select Upload.

k.  Upload the transcribe-sample.mp3 file by selecting Add files and selecting the file OR dragging the transcribe-sample.mp3 file to the upload box.

Select Upload.

l.  Select the checkbox next to the transcribe-sample.mp3 file in your bucket. A file detail pane will be displayed for the transcribe-sample.mp3 file. Copy the link to the file and save it for use later in the tutorial.

a.  From the top menu bar, select Services then begin typing Transcribe in the search bar and select Amazon Transcribe to open the service console.

b.  On the Amazon Transcribe console main page, open the navigation pane and click Transcription jobs.

c. On the Transcription jobs page, click Create job.

d.  On the Create transcription job page, in the Name field, type sample-transcription-job.

Leave the default Language as English.

In the Input file location on S3 field, paste the link to the sample file in your S3 bucket. The link to your sample file will be different than the one shown in the screenshot to the right.  

Leave the default Format of mp3.

You can use the Custom vocabulary feature to help Amazon Translate recognize words and phrases that are specific to your application, such as a non-English name like Etienne. You won't use this feature in this tutorial.

e.  Leave the default Data location as Amazon default.

if you enable Channel identification, Amazon Transcribe is able to process audio where each speaker is recorded on different channels and produce a single transcript annotated with channel labels.

If you enable Speaker identification, Amazon Transcribe recognizes when the speaker changes and attributes the transcribed text appropriately.

Neither of these options is used in this tutorial.

Select Create to start your transcription job.  

a.  After you click the Create button, you will be taken to the Transcription jobs screen. It will show the status of sample-transcription-job. The status can be In progress, Complete, or Failed.

When the status is Complete, click on the sample-transcription-job link in the Name column to view the transcription results.

b.   Next you will see the sample-transcription-job details. Scroll down to the Transcription panel to view the transcription job output. In the JSON pane you can view the transcription results as it would be returned from the Transcribe API or AWS CLI.

a.  In this upper navigation menu, click on Services and begin typing S3 in the search bar and select S3 to open the console.

b.  Scroll through your S3 buckets and find the bucket that you created earlier in this tutorial. Click on this bucket name to view the contents of the bucket. Your bucket name will be different in the screenshot to the right.

c.  Select the transcribe-sample.mp3 file contained within your bucket and from the Actions menu select Delete. Confirm the deletion.